Abstract: The present invention relates to a polyester sound absorption material having improved moldability and decreased weight and a method of manufacturing a molded product using the same, and more particularly to a polyester sound absorption material, which is capable of integrally molding a skin member and a sound absorption material using a felt including a polyester base fiber, a low-melting-point polyester adhesive fiber and a polyester hollow fiber, without the need to attach an additional sound absorption pad onto a skin member.

Abstract: The present invention relates to the acoustic metamaterial structural unit with the function of soundproof, flow-passing and heat-transferring enhancement, which comprises a frame, a constraint placed in the frame and a piece of membrane covering at least one surface of the frame; both the frame and the membrane are respectively placed at least one hole. Besides, the present invention also provides the acoustic metamaterial composite plate and the composite structure constructed with the acoustic metamaterial structural unit; the method for adjusting the frequency and the assemble method. The present structural unit possesses better soundproof property than the routine perforated plated or micro-perforated plate in broad operating frequency. And also the enough heat flow, gas flow or fluid flow can pass through smoothly.

Abstract: A vibration reducing device is attached to a structure and blocks sound transmitted through the structure. The vibration reducing device includes a unit structure having a target frequency band, the unit structure including a plurality of unit cells, each formed of an acoustic meta-material and having a different target frequency, the unit cells being connected through first bridges; and a predetermined number of unit structures being connected through second bridges and attached to the structure, where each of the unit cells comprises: a mass portion of which a size is set according to the target frequency; a base frame formed as a quadrangular frame, the mass portion being eccentrically disposed in the base frame; and a support portion that connects the mass portion and the base frame, the support portion having a size that is set according to the target frequency.

Abstract: A hearing device comprises a forward path comprising an input transducer providing at an electric input signal representative of environment sound, a signal processor for processing said at least one electric input signal and providing a processed signal, and a loudspeaker connected to a speaker sound outlet providing an output sound to an eardrum of the user in dependence of said processed signal. The hearing device comprises an ITE-part adapted for being located in an ear canal of the user, an active emission canceller providing an electric sound cancelling signal, and an environment facing loudspeaker providing an output sound to the environment. The electric sound cancelling signal is determined in dependence of said processed signal to attenuate sound leaked from the speaker sound outlet to the environment when played by the environment facing loudspeaker. The environment facing loudspeaker has a sound outlet on an environment facing surface of the ITE-part.

Abstract: A method and a system for creating a plurality of sound zones within an acoustic cavity is provided. The method comprises: providing a plurality of actuators within the acoustic cavity, each for generating a respective acoustic output in response to a respective drive signal, providing, for each of the plurality of actuators, an adaptive filter for receiving a respective input signal, and generating a respective output signal, providing, for each of the adaptive filters, at least one filter coefficient, providing a plurality of error sensors within the acoustic cavity, each for generating a respective error signal e, representing a respective sound detected by the respective error sensor, providing an audio data signal x(n) for generating a desired sound in a desired sound zone of the plurality of sound zones, determining, for the desired sound zone, a set of actuator generation coefficients kgk, a set of actuator exclusion coefficients kek, wherein k refers to a kth actuator, k=1, 2, 3 . . .

Abstract: An audio system for an ear mountable playback device includes a speaker, an error microphone, which senses sound being output from the speaker, and a sound control processor. The processor is configured for controlling and/or monitoring a playback of a detection signal or a filtered version of the detection signal via the speaker, recording an error signal from the error microphone, and determining whether the playback device is in a first state, where the playback device is worn by a user, or in a second state, where the playback device is not worn by a user, based on processing of the error signal.

Abstract: The present technology relates to a signal processing device, a signal processing method, and a program that allow for easier sound source separation. The signal processing device includes a sound source separation unit that recursively performs sound source separation on an input acoustic signal by using a predetermined sound source separation model learned in advance to separate a predetermined sound source from an acoustic signal for learning including the predetermined sound source. The present technology can be applied to a signal processing device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating speech from text. One of the systems includes one or more computers and one or more storage devices storing instructions that when executed by one or more computers cause the one or more computers to implement: a sequence-to-sequence recurrent neural network configured to: receive a sequence of characters in a particular natural language, and process the sequence of characters to generate a spectrogram of a verbal utterance of the sequence of characters in the particular natural language; and a subsystem configured to: receive the sequence of characters in the particular natural language, and provide the sequence of characters as input to the sequence-to-sequence recurrent neural network to obtain as output the spectrogram of the verbal utterance of the sequence of characters in the particular natural language.

Abstract: The present disclosure is related to systems and methods for processing speech dialogue. The method includes obtaining target speech dialogue data. The method includes obtaining a text vector representation sequence, a phonetic symbol vector representation sequence, and a role vector representation sequence by performing a vector transformation on the target speech dialogue data based on a text embedding model, a phonetic symbol embedding model, and a role embedding model, respectively. The method includes determining a representation vector corresponding to the target speech dialogue data by inputting the text vector representation sequence, the phonetic symbol vector representation sequence, and the role vector representation sequence into a trained speech dialogue coding model. The method includes determining a summary of the target speech dialogue data by inputting the representation vector into a classification model.

Abstract: A computer system is provided that includes a processor configured to store a set of audio training data that includes a plurality of audio segments and metadata indicating a word or phrase associated with each audio segment. For a target training statement of a set of structured text data, the processor is configured to generate a concatenated audio signal that matches a word content of a target training statement by comparing the words or phrases of a plurality of text segments of the target training statement to respective words or phrases of audio segments of the stored set of audio training data, selecting a plurality of audio segments from the set of audio training data based on a match in the words or phrases between the plurality of text segments of the target training statement and the selected plurality of audio segments, and concatenating the selected plurality of audio segments.

Abstract: A method for processing multi-modal input includes receiving multiple signal inputs, each signal input having a corresponding input mode. Each signal input is processed in a series of mode-specific processing stages. Each successive mode-specific stage is associated with a successively longer scale of analysis of the signal input. A fused output is generated based on the output of a series of fused processing stages. Each successive fused processing stage is associated with a successively longer scale of analysis of the signal input. Multiple fused processing stages receive inputs from corresponding mode-specific processing stages, so that the fused output depends on the multiple of signal inputs.

Abstract: Audio signals of speech may be processed using an acoustic model. An acoustic model may be implemented with multiple streams of processing where different streams perform processing using different dilation rates. For example, a first stream may process features of the audio signal with one or more convolutional neural network layers having a first dilation rate, and a second stream may process features of the audio signal with one or more convolutional neural network layers having a second dilation rate. Each stream may compute a stream vector, and the stream vectors may be combined to a vector of speech unit scores, where the vector of speech unit scores provides information about the acoustic content of the audio signal. The vector of speech unit scores may be used for any appropriate application of speech, such as automatic speech recognition.

Abstract: A system for providing information to a user includes and/or interfaces with a set of models and/or algorithms. Additionally or alternatively, the system can include and/or interface with any or all of: a processing subsystem; a sensory output device; a user device; an audio input device; and/or any other components. A method for providing information to a user includes and/or interfaces with: receiving a set of inputs; processing the set of inputs to determine a set of sensory outputs; and providing the set of sensory outputs.

Abstract: Systems and methods to analyze contacts data. Contacts data may be encoded as text (e.g., chat logs), audio (e.g., audio recordings), and various other modalities. A computing resource service provider may implement a service to obtain audio data from a client, transcribe the audio data, thereby generating text, execute one or more natural language processing techniques to generate metadata associated with the text, processing at least the metadata to generate an output, determine whether the output matches one or more categories, and provide the output to the client. Techniques described herein may be performed as an asynchronous workflow.

Abstract: Techniques for decreasing (or eliminating) the possibility of a skill performing an action that is not responsive to a corresponding user input are described. A system may train one or more machine learning models with respect to user inputs, which resulted in incorrect actions being performed by skills, and corresponding user inputs, which resulted in the correct action being performed. The system may use the trained machine learning model(s) to rewrite user inputs that, if not rewritten, may result in incorrect actions being performed. The system may implement the trained machine learning model(s) with respect to ASR output text data to determine if the ASR output text data corresponds (or substantially corresponds) to previous ASR output text data that resulted in an incorrect action being performed.

Abstract: A skill dispatching method for a speech dialogue platform including: receiving, by a central control dispatching service, a semantic result of recognizing a user's voice sent by a data distribution service; dispatching, by the central control dispatching service, a plurality of skill services related to the semantic result in parallel, and obtaining skill parsing results from the plurality of skill services; sorting the skill parsing results based on priorities of the skill services, and exporting a result with the highest priority to a skill realization discrimination service; when failure in realization, selecting a result with the highest priority among the rest of skill parsing results and exporting the same to the skill realization discrimination service, and when success in realization, sending the result with the highest priority to the data distribution service for feedback to the user. The method improves skill dispatching efficiency, reduces delay, and improves user experience.

Abstract: Systems and processes for operating a digital assistant are provided. In an example process, low-latency operation of a digital assistant is provided. In this example, natural language processing, task flow processing, dialogue flow processing, speech synthesis, or any combination thereof can be at least partially performed while awaiting detection of a speech end-point condition. Upon detection of a speech end-point condition, results obtained from performing the operations can be presented to the user. In another example, robust operation of a digital assistant is provided. In this example, task flow processing by the digital assistant can include selecting a candidate task flow from a plurality of candidate task flows based on determined task flow scores. The task flow scores can be based on speech recognition confidence scores, intent confidence scores, flow parameter scores, or any combination thereof. The selected candidate task flow is executed and corresponding results presented to the user.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method, and computer program product embodiments for adapting an automated speech recognition system to provide more accurate suggestions to voice queries involving media content including recently created or recently available content. An example computer-implemented method includes transcribing the voice query, identifying respective components of the query such as the media content being requested and the action to be performed, and generating fuzzy candidates that potentially match the media content based on phonetic representations of the identified components. Phonetic representations of domain specific candidates are stored in a domain entities index and is continuously updated with new entries so as to maintain the accuracy of the speech recognition of voice queries for recently created or recently available content.

Abstract: An audio controlled assistant captures environmental noise and converts the environmental noise into audio signals. The audio signals are provided to a system which analyzes the audio signals for a plurality of audio prompts, which have been customized for the acoustic environment surrounding the audio controlled assistant by an acoustic modeling system. The system configured to detect the presence of an audio prompt in the audio signals and transmit instructions associated with the detected audio prompt to at least one of the audio controlled assistant or one or more cloud based services, in response.

Abstract: An approach for controlling method of an electronic device is provided. The approach acquires voice information and image information for setting an action to be executed according to a condition, the voice information and the image information being respectively generated from a voice and a behavior associated with the voice of a user. The approach determines an event to be detected according to the condition and a function to be executed according to the action when the event is detected, based on the acquired voice information and the acquired image information. The approach determines at least one detection resource to detect the determined event. In response to the at least one determined detection resource detecting at least one event satisfying the condition, the approach executes the function according to the action.

Abstract: A method includes a first assistant-enabled device (AED) receiving an assignment instruction assigning a group hotword to a selected group of AEDs that includes the first AED and one or more other AEDs. Each AED is configured to wake-up from a low-power state when the group hotword is detected in streaming audio by at least one of the AEDs. The method also includes receiving audio data that corresponds to an utterance spoken by the user and includes a query that specifies an operation to perform. In response to detecting the group hotword in the audio data, the method also includes triggering the first AED to wake-up from the low-power state and executing a collaboration routine to cause the first AED and each other AED in the selected group of AEDs to collaborate with one another to fulfill performance of the operation specified by the query.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to providing talk back automation for applications installed on a mobile device. To do so actions (e.g., talk back features) can be created, via the digital assistant, by recording a series of events that are typically provided by a user of the mobile device when manually invoking the desired action. At a desired state, the user may select an object that represents the output of the application. The recording embodies the action and can be associated with a series of verbal commands that the user would typically announce to the digital assistant when an invocation of the action is desired. In response, the object is verbally communicated to the user via the digital assistant, a different digital assistant, or even another device. Alternatively, the object may be communicated to the same application or another application as input.

Abstract: In some examples, a software agent executing on a server receives a communication comprising a first utterance from a customer and predicts, using an intent classifier, a first intent of the first utterance. Based on determining that the first intent is order-related, the software agent predicts, using a dish classifier, a cart delta vector based at least in part on the first utterance and modifies a cart associated with the customer based on the cart delta vector. The software agent predicts, using a dialog model, a first dialog response based at least in part on the first utterance and provides the first dialog response to the customer using a text-to-speech converter.

Abstract: A method for controlling a device includes: collecting audio data where the device is located; determining whether each target frame of the audio data is a first type signal; in response to the target frame of the audio data being the first type signal, determining an acoustic event type represented by the first type signal; and controlling the device to execute control instructions corresponding to the acoustic event type.

Abstract: A system and method establishes a communication connection between a first device of a first user and a second device of a second user. Request data corresponding to a request to establish a communication connection with a second user is received, and a user profile associated with the second user is determined. One or more sensors of the second device receive input data corresponding to the environment of the second device, and an identity of the second user is determined based thereon. The communication connection is established and, based on the identity, the second device tracks movement of the second user in the environment.

Abstract: A control method for a display system is provided. The display system includes a display device displaying an image, and a voice processing device which generates first voice data based on a first voice requesting a first-type operation belonging to a part of a plurality of types of operations to the display device and transmits the first voice data to a server device. The display device receives a command to execute the first-type operation from the server device. The display device includes a voice recognition unit recognizing a second voice requesting a second-type operation that is different from the first-type operation, and a control unit controlling execution of the first-type operation and the second-type operation. The voice processing device transmits the first voice data requesting a permission for the execution of the second-type operation, to the server device. The display device receives a command permitting the execution of the second-type operation from the server device.

Abstract: As noted above, example techniques relate to toggling a cloud-based VAS between enabled and disabled modes. An example implementation involves a NMD detecting that the housing is in a first orientation and enabling a first mode. Enabling the first mode includes disabling voice input processing via a cloud-based VAS and enabling local voice input processing. In the first mode, the NMD captures sound data associated with a first voice input and detects, via a local natural language unit, that the first voice input comprises sound data matching one or more keywords. The NMD determines an intent of the first voice input and performs a first command according to the determined intent. The NMD may detect that the housing is in a second orientation and enables the second mode. Enabling the second mode includes enabling voice input processing via the cloud-based VAS.

Abstract: A processing system detects a period of non-voice activity and compares its duration to a cutoff period. The system adapts the cutoff period based on parsing previously-recognized speech to determine, according to a model, such as a machine-learned model, the probability that the speech recognized so far is a prefix to a longer complete utterance. The cutoff period is longer when a parse of previously recognized speech has a high probability of being a prefix of a longer utterance.

Abstract: A method of controlling a battery-powered remote controller to decrease a duty cycle to allow continued operations despite the quantity of the battery is bad determines a drop in voltage of the battery in standby mode as voltage of the battery is being read. When receiving a command to activate a voice function, determining whether the drop in voltage in standby mode is greater than or equal to a preset value. If yes, the method then determines whether the drop in voltage falls in a preset range. If yes, the method regulates a duty cycle of the pulse signal activating the voice function, and activates the voice function as required. A remote controller and a non-transitory storage medium are also provided.

Abstract: Methods and systems for natural language processing/understanding of voice conversations are provided. Using natural language processing, a clinical condition is extracted from a voice conversation. A clinical ontology identifies clinical concepts associated with the clinical conditions. The clinical concepts are classified for documentation. The clinical concepts are searched and validated from within an individual's longitudinal record.

Abstract: A system is provided that can provide a virtual assistant that can receive inputs from a user and can provide responses to the user. The system can perform natural language processing on the inputs to process the inputs into inputs that are comprehendible by the virtual assistant. The system can predict, based on the inputs, at least one objective of the user. The at least one objective can include a first objective for communication with a live agent and the at least one objective can include a second objective for a purpose for the communication with the live agent. Additionally, the system can determine the live agent that can be best suited to assist the user based on the second objective. The system can connect the user and the live agent. The virtual assistant can facilitate the connection by providing information to the user and to the live agent.

Abstract: A display apparatus includes an input unit configured to receive a user command; an output unit configured to output a registration suitability determination result for the user command; and a processor configured to generate phonetic symbols for the user command, analyze the generated phonetic symbols to determine registration suitability for the user command, and control the output unit to output the registration suitability determination result for the user command. Therefore, the display apparatus may register a user command which is resistant to misrecognition and guarantees high recognition rate among user commands defined by a user.

Abstract: A spoken dialogue device includes a recognition unit that recognizes an acquired user speech, a barge-in speech control unit that determines whether to engage a barge-in speech, a dialogue control unit that outputs a system response to a user based on a recognition result of the user speech other than the barge-in speech determined not to be engaged by the barge-in speech control unit, a response generation unit that generates a system speech based on the system response, and an output unit that outputs a system speech. When each user speech element included in the user speech corresponds to a predetermined morpheme included in the immediately previous system speech and does not correspond to a response candidate to the immediately previous system speech by a user, the barge-in speech control unit does not engage at least the user speech element.

Abstract: Participants may use one or more devices for engaging in a meeting, such as phones, conferencing devices, and/or computers. The devices include microphones that capture speech for determining the presence of distinct participants. Speech signals originating from different participants, or microphones, may be determined and associated with the participants. For example, microphones may be directional and more sensitive to sound coming from one or more specific directions than sound coming from other directions. By associating an individual with a microphone, or set of microphones, overlapping voices may be disambiguated to provide clear voice streams that aid in producing a clear transcript indicating the speech of the participants, respectively. An identity of the participants may be determined using voiceprint and/or voice recognition techniques.

Abstract: Providing speech-to-text (STT) transcription by a user endpoint device includes initiating an audio communication between an enterprise server and the user endpoint device, the audio communication comprising a voice interaction between a user associated with the user endpoint device and an agent associated with an agent device to which the enterprise server routes the audio communication; performing a first STT of at least a portion of the voice interaction to produce a first transcribed speech in a first language; concurrent with performing the first STT, performing, by the user endpoint device, a second STT of the at least the portion of the voice interaction to produce a second transcribed speech in a second language different than the first language, and transmitting the at least the portion of the voice interaction and at least the first transcribed speech from the user endpoint device to the enterprise server.

Abstract: A system is provided for determining privacy controls for output including sensitive data. A user may subscribe to receive an output in the future based on the occurrence of an event. The system may determine when the event is occurred triggering the output, and determine that the output includes outputting sensitive data. The system may determine output data that does not include the sensitive data, send the output data to a device, and may request the user to provide an authentication input to receive the sensitive data.

Abstract: An apparatus includes a processor to: receive, from a requesting device, a request to perform speech-to-text conversion of a speech data set; within a first thread of a thread pool, perform a first pause detection technique to identify a first set of likely sentence pauses; within a second thread of the thread pool, perform a second pause detection technique to identify a second set of likely sentence pauses; perform a speaker diarization technique to identify a set of likely speaker changes; divide the speech data set into data segments representing speech segments based on a combination of at least the first set of likely sentence pauses, the second set of likely sentence pauses, and the set of likely speaker changes; use at least an acoustic model with each data segment to identify likely speech sounds; and generate a transcript based, at least in part, on the identified likely speech sounds.

Abstract: Systems, methods, and devices provide a user experience capable of integrating robo-advising with human advising based on various inputs that are actively detected. Inputs from a conversation, or multiple conversations separated in time, may be analyzed to determine, based on voice inputs, that live communications should be initiated. Based on triggers identified, a robo-advising session may additionally or alternatively be initiated. Transitions between advising sessions may be facilitated to allow users to more efficiently employ robo-advising until human advising is triggered.

Abstract: In an embodiment, an integrated circuit may include one or more CPUs, a memory controller, and a circuit configured to remain powered on when the rest of the SOC is powered down. The circuit may be configured to receive audio samples from a microphone, and match those audio samples against a predetermined pattern to detect a possible command from a user of the device that includes the SOC. In response to detecting the predetermined pattern, the circuit may cause the memory controller to power up so that audio samples may be stored in the memory to which the memory controller is coupled. The circuit may also cause the CPUs to be powered on and initialized, and the operating system (OS) may boot. During the time that the CPUs are initializing and the OS is booting, the circuit and the memory may be capturing the audio samples.

Abstract: Techniques for processing voice commands from a locked device are described. A voice command received by a locked device is stored, a prompt requesting that the device be unlocked is generated, and the voice command is processed automatically after the device is unlocked. Thus, the system processes the voice command without the user repeating the voice command. In addition, the system may process certain voice commands even when the device is locked. For example, a whitelist filter compares an intent associated with the voice command to whitelisted intents from a whitelist database before the intent is dispatched to a speechlet, and intents included in the whitelist database are processed normally. Thus, the system performs certain voice commands while the device is locked, while other voice commands may be automatically processed after the device is unlocked without the user repeating the voice command.

Abstract: One or more computing devices, systems, and/or methods for user identification and authorization are provided. In an example, a voice command to perform an action is detected. A voice profile associated with a user is identified based upon voice characteristics of the voice command. In response to determining that the voice profile is not linked to an account associated with the action, the user is prompted for an identifier associated with a device for creating the account through the device. In response to receiving the identifier from the user, the identifier is utilized to facilitate creation of the account through the device.

Abstract: Techniques are provided for reverberation compensation for far-field speaker recognition. A methodology implementing the techniques according to an embodiment includes receiving an authentication audio signal associated with speech of a user and extracting features from the authentication audio signal. The method also includes scoring results of application of one or more speaker models to the extracted features. Each of the speaker models is trained based on a training audio signal processed by a reverberation simulator to simulate selected far-field environmental effects to be associated with that speaker model. The method further includes selecting one of the speaker models, based on the score, and mapping the selected speaker model to a known speaker identification or label that is associated with the user.

Abstract: Embodiments described herein provide for systems and methods for implementing a neural network architecture for spoof detection in audio signals. The neural network architecture contains a layers defining embedding extractors that extract embeddings from input audio signals. Spoofprint embeddings are generated for particular system enrollees to detect attempts to spoof the enrollee's voice. Optionally, voiceprint embeddings are generated for the system enrollees to recognize the enrollee's voice. The voiceprints are extracted using features related to the enrollee's voice. The spoofprints are extracted using features related to features of how the enrollee speaks and other artifacts. The spoofprints facilitate detection of efforts to fool voice biometrics using synthesized speech (e.g., deepfakes) that spoof and emulate the enrollee's voice.

Abstract: An electronic device and method are provided. The method includes identifying a speech section of a user and a speech section of a neighbor in a received audio signal, identifying a user utterance in the speech section of the user and a neighbor answer to the user utterance in the speech section of the neighbor, obtaining preference information associated with the user utterance, giving a first reliability to the neighbor answer and a second reliability to an agent answer of an artificial intelligence agent generated in response to the user utterance, based on the preference information, not responding to the user utterance when the second reliability is lower than the first reliability, and outputting the agent answer when the second reliability is equal to or higher than the first reliability.

Abstract: A system may receive a communication from a user, which may include a vocal sample. The system may transform the vocal sample from a wavelength domain into a frequency domain. The system may determine a divergence of one or more amplitude values of the transformed frequency domain from a predetermined frequency distribution. According to some embodiments, the predetermined frequency distribution may be a Benford's distribution. When the divergence exceeds a predetermined threshold, the system may execute one or more security measures. The one or more security measures may include (i) transferring the user from an automated operator to a human operator, (ii) requiring second factor authentication from the user, and/or (iii) denying a user-initiated request.

Abstract: A method, decoder, and program code for controlling a concealment method for a lost audio frame is provided. A first audio frame and a second audio frame of the received audio signal are decoded to obtain modified discrete cosine transform (MDCT) coefficients. Values of a first spectral shape based upon the MDCT coefficients decoded from the first audio frame decoded and values of a second spectral shape based upon MDCT coefficients decoded from the second audio frame decoded are determined, the spectral shapes each comprising a number of sub-bands. The values of the spectral shapes and frame energies of the first audio frame and second audio frame are transformed into representations of FFT based spectral analyses. A transient condition is detected based on the representations of the FFTs. Responsive to detecting the transient condition, the concealment method is modified by selectively adjusting a spectrum magnitude of a substitution frame spectrum.

Abstract: A method for generation of comfort noise for at least two audio channels. The method comprises determining a spatial coherence between audio signals on the respective audio channels, wherein at least one spatial coherence value per frame and frequency band is determined to form a vector of spatial coherence values. A vector of predicted spatial coherence values is formed by a weighted combination of a first coherence prediction and a second coherence prediction that are combined using a weight factor ?. The method comprises signaling information about the weight factor ? to the receiving node, for enabling the generation of the comfort noise for the at least two audio channels at the receiving node.

Abstract: A frequency-domain audio codec is provided with the ability to additionally support a certain transform length in a backward-compatible manner, by the following: the frequency-domain coefficients of a respective frame are transmitted in an interleaved manner irrespective of the signalization signaling for the frames as to which transform length actually applies, and additionally the frequency-domain coefficient extraction and the scale factor extraction operate independent from the signalization. By this measure, old-fashioned frequency-domain audio coders/decoders, insensitive for the signalization, would be able to nevertheless operate without faults and with reproducing a reasonable quality. Concurrently, frequency-domain audio coders/decoders able to support the additional transform length would offer even better quality despite the backward compatibility.

Abstract: An audio signal encoding and decoding method using a neural network model, a method of training the neural network model, and an encoder and decoder performing the methods are disclosed. The encoding method includes computing the first feature information of an input signal using a recurrent encoding model, computing an output signal from the first feature information using a recurrent decoding model, calculating a residual signal by subtracting the output signal from the input signal, computing the second feature information of the residual signal using a nonrecurrent encoding model, and converting the first feature information and the second feature information to a bitstream.

Abstract: An apparatus for processing an encoded audio signal, which includes a sequence of access units, each access unit including a core signal with a first spectral width and parameters describing a spectrum above the first spectral width, has a demultiplexer generating, from an access unit of the encoded audio signal, the core signal and a set of the parameters, an upsampler upsampling the core signal of the access unit and outputting a first upsampled spectrum and a timely consecutive second upsampled spectrum, the first upsampled spectrum and the second upsampled spectrum, both, having a same content as the core signal and having a second spectral width being greater than the first spectral width of the core spectrum, a parameter converter converting parameters of the set of parameters of the access unit to obtain converted parameters, and a spectral gap filling processor processing the first upsampled spectrum and the second upsampled spectrum using the converted parameters.