Abstract: A computer-implemented method for correcting muffled speech caused by facial coverings is disclosed. The computer-implemented method includes monitoring a user's speech for speech distortion. The computer-implemented method further includes determining that the user's speech is distorted. The computer-implemented method further includes determining that a cause of the user's speech distortion is based, at least in part, on a presence of a particular type of facial covering. The computer-implemented method further includes automatically correcting the speech distortion of the user based, at least in part, on the particular type of facial covering causing the speech distortion.

Abstract: Techniques for communications in a multi-zone space are described. In an example, a system stores data indicating devices in zones of a space and data indicating zones that are associated with a communications session. A display in a zone presents graphical user interface indicating the zones associated with the communications session. Incoming audio data can be mixed with audio data detected from another participating zone and a speaker in the zone can output this audio data. Audio data detected from the participating zone can also be mixed and sent to a remote device that is an endpoint of the communications session.

Abstract: Techniques are disclosed that enable processing of audio data to generate one or more refined versions of audio data, where each of the refined versions of audio data isolate one or more utterances of a single respective human speaker. Various implementations generate a refined version of audio data that isolates utterance(s) of a single human speaker by processing a spectrogram representation of the audio data (generated by processing the audio data with a frequency transformation) using a mask generated by processing the spectrogram of the audio data and a speaker embedding for the single human speaker using a trained voice filter model. Output generated over the trained voice filter model is processed using an inverse of the frequency transformation to generate the refined audio data.

Abstract: Voice processing method and device includes obtaining a probability value of an audio signal representing sound, collected by a first microphone on a near-end side, including a person's voice, determining a gain of the audio signal based on the determined probability value, processing the audio signal based on the determined gain of the audio signal, and sending the processed audio signal to a far-end side.

Abstract: Disclosed is an electronic device. The electronic device includes: an audio output device comprising circuitry configured to output a sound; a microphone; and a processor configured to control, based on a content being selected, the audio output device to output an audio signal corresponding to the content using a sound compensation value, wherein the processor is configured to: extract, based on a sound corresponding to the content being output from the audio output device and input to the microphone, characteristic information from the sound input to the microphone, calculate a sound compensation value based on the extracted characteristic information, and update the sound compensation value with the calculated sound compensation value.

Abstract: A signal processing apparatus according an embodiment includes an acquisition unit and an application unit. The acquisition unit acquires M detection signals output from M detector devices having N-fold symmetry (M is an integer equal to or greater than 2, and N is an integer equal to or greater than 2). Each of the M detector devices detects original signals generated from K signal sources (K is an integer equal to or greater than 2) having the N-fold symmetry. The application unit applies a trained neural network to M input vectors corresponding to the M detection signals and outputs K output vectors. The same parameter is set to, of multiple weights included in a weight matrix of the trained neural network, weights that are commutative based on the N-fold symmetry.

Abstract: A sound muffling chamber covers a nose and mouth in an airtight manner. The sound muffling chamber includes a microphone that detects vocal sound waves in the sound muffling chamber and generates a voice signal. A digital signal processing system analyzes the voice signal and generates a voice cancellation signal. A sound silencing chamber includes a speaker that generates out of phase sound waves in response to the voice cancellation signal that superimposes on and cancels the vocal sound waves. A sound decelerator is positioned between the sound muffling chamber and the sound silencing chamber and configured to increase a traveling time of the vocal sound waves such that the vocal sound waves' arrival at the sound silencing chamber may be synchronized with the arrival of a voice cancellation signal. The sound muffling chamber may include inflatable cells separated by slats such that the sound muffling chamber is foldable.

Abstract: A controlling method of a wearable electronic apparatus includes: receiving, by an IMU sensor, a bone conduction signal corresponding to vibration in the user's face, while the wearable electronic apparatus is operated in an ANC mode; identifying a presence or an absence of the user's voice based on the bone conduction signal; based on the identifying the presence of the user's voice, controlling an operation mode of the wearable electronic apparatus to be a different operation mode from the ANC mode; while the wearable electronic apparatus is operated in the different operation mode, identifying presence or absence of the user's voice based on the bone conduction signal; and based on the absence of the user's voice being identified for a predetermined time while the wearable electronic apparatus is operated in the different operation mode, controlling the different operation mode to return to the ANC mode.

Abstract: At a first layer of an echo canceler, a first compensation for a first set of properties of output of an audio capture device of a first communication environment is applied. The first set of properties includes a property resulting from a difference in clock speeds of an audio capture device and an audio rendering device of the first communication environment. At a second layer of the echo canceler, at which output of the first layer is received, a second compensation for a second set of properties of the output of the first layer is applied. The second set of properties includes an echo. Applying the compensations comprises modifying neural network weights. Output of the second layer is transmitted to a second communication environment.

Abstract: A baby monitor system with white noise filtering comprises a camera unit and a monitor unit, wherein the camera unit is predefined soothing sounds and play at least one of the predefined soothing sounds for baby; the camera unit records the mixture sound of baby, ambient noises and white noises and transforms the mixture sound to sound features, wherein the white noises at least include the soothing sounds and stationary noise; the recorded sound features are compared to local audio features of the predefined soothing sounds; if there are matching features between the recorded sound features and the local audio features, removing the matching features from the recorded sound features; the stationary noise features are extracted and removed from the recorded sound features; the camera unit outputs the recorded mixture sound without the white noise to the monitor unit.

Abstract: Developed and presented herein are embodiments of a new end-to-end approach for audio denoising, from a synthesis perspective. Instead of explicitly modelling the noise component in the input signal, embodiments directly synthesize the denoised audio from a generative model (or vocoder), as in text-to-speech systems. In one or more embodiments, to generate the phonetic contents for the autoregressive generative model, it is learned via a variational autoencoder with discrete latent representations. Furthermore, in one or more embodiments, a new matching loss is presented for the denoising purpose, which is masked on when the corresponding latent codes differ. As compared against other method on test datasets, embodiments achieve competitive performance and can be trained from scratch.

Abstract: Systems and methods for establishing user persona from audio interactions are disclosed, including a voice-based conversational AI platform having an acoustic analytical record engine and audio signal codification optimizer. The engine receives an audio sample indicative of voice conversation between an end user and a bot and transforms it into quantifiable and machine-ingestible power spectrum and acoustic indicators that uniquely represent the audio sample in the form of a feature vector. The optimizer ingests and processes the indicators to estimate likelihood of an attribute value representing the audio sample by constructing a convolutional neural network model for each attribute category. The optimizer establishes user persona attribute values across different attribute categories for the audio sample based on the estimated likelihood.

Abstract: A method includes receiving sound input features representative of sound received during an electronic conference, the sound including voice and input device activation sound, receiving an input event feature indicative of the input device activation, and processing the received sound input features and input event feature via a trained model to identify a stored spectral file to be subtracted from the received sound to suppress the input device activation sound.

Abstract: An apparatus for decomposing an audio signal into a background component signal and a foreground component signal, has: a block generator for generating a time sequence of blocks of audio signal values; an audio signal analyzer for determining a characteristic of a current block of the audio signal and for determining a variability of the characteristic within a group of blocks having at least two blocks of the sequence of blocks; and a separator for separating the current block into a background portion and a foreground portion wherein the separator is configured to determine a separation threshold based on the variability and to separate the current block into the background component signal and the foreground component signal, when the characteristic of the current block is in a predetermined relation to the separation threshold.

Abstract: An audio system presents enhanced audio content to a user of a headset. The audio system detects sounds from the local area, at least a portion of which originate from a human sound source. The audio system obtains a voice profile of an identifies human sound source that generates at least the portion of the detected sounds. Based in part on the voice profile, the audio system enhances the portion of the detected sounds that are generated by the human sound source to obtain enhanced audio. The audio system presents the enhanced audio to the user.

Abstract: An encoder for providing an audio stream on the basis of a transform-domain representation of an input audio signal includes a quantization error calculator configured to determine a multi-band quantization error over a plurality of frequency bands of the input audio signal for which separate band gain information is available. The encoder also includes an audio stream provider for providing the audio stream such that the audio stream includes information describing an audio content of the frequency bands and information describing the multi-band quantization error. A decoder for providing a decoded representation of an audio signal on the basis of an encoded audio stream representing spectral components of frequency bands of the audio signal includes a noise filler for introducing noise into spectral components of a plurality of frequency bands to which separate frequency band gain information is associated on the basis of a common multi-band noise intensity value.

Abstract: Disclosed are systems and methods for automatic control of gain in audio and video conferencing applications to maintain a predetermined and stable audio level. In one embodiment, a first stage applies a first stage gain based on a long-term estimate of signal level, while a second stage gain, based on a short-term estimate of signal level assists the first stage gain to achieve a target level. Some embodiments of long-term level estimation utilize statistical analysis of a buffer to validate or arrive at a more accurate long-term signal level estimate.

Abstract: Apparatuses and methods of transmitting and receiving a speech signal. The method of transmitting a speech signal includes extracting low frequency feature information from an input speech signal by using a first feature extracting network; and transmitting a speech signal corresponding to the low frequency feature information to a receiving end. The method of receiving a speech signal includes receiving a first speech signal transmitted by a transmitting end; extracting low frequency feature information from the first speech signal and recovering high frequency feature information based on the low frequency feature information, by using a second feature extracting network; and outputting a second speech signal including the low frequency feature information and the high frequency feature information.

Abstract: A method of processing an acoustic signal is disclosed. According to one or more embodiments, a first acoustic signal is received via a first microphone. The first acoustic signal is associated with a first speech of a user of a wearable headgear unit. A first sensor input is received via a sensor, a control parameter is determined based on the sensor input. The control parameter is applied to one or more of the first acoustic signal, the wearable headgear unit, and the first microphone. Determining the control parameter comprises determining, based on the first sensor input, a relationship between the first speech and the first acoustic signal.

Abstract: A smart mask includes a main body having a back frame and a front cover. The back frame and the front cover each include an opening that is aligned with the mask wearer's mouth when worn. The front cover and back frame may be detachable from one another, or a single piece. A microphone is provided in the main body, as well as a speaker. A processor located in the main body is connected to the microphone and the speaker, and is configured to enhance the speech of the mask wearer. In particular, the processor receives audio signals representing a transformation of a spoken utterance of the wearer, processes the audio signals to enhance the speech, and then outputs the enhanced speech to the speaker. This helps other people better understand what the mask wearer is saying.

Abstract: A method, computer program product, and computing system for receiving a speech signal from each microphone of a plurality of microphones, thus defining a plurality of signals. One or more noise signals associated with microphone self-noise may be received. One or more self-noise-based augmentations may be performed on the plurality of signals based upon, at least in part, the one or more noise signals associated with microphone self-noise, thus defining one or more self-noise-based augmented signals.

Abstract: A transient detector analyzes a given frame n of the input audio signal to determine, based on audio signal characteristics of the given frame n, a transient hangover indicator for a following frame n+1, and signals the determined transient hangover indicator to an associated audio encoder to enable proper encoding of the following frame n+1.

Abstract: Systems and methods are disclosed herein for modifying modulated signals for transmission. The system receives a modulated signal comprising a speech signal and a carrier wave and generates first and second spectral signals by converting the modulation signal and carrier wave from the time domain to the frequency domain respectively. The system then determines spectral bands for the first and second spectral signals. For each spectral band, the system calculates a weighted spectral band value based on a magnitude of the first spectral signal within the spectral band and generates a modified spectral signal by modifying the second spectral signal with the weighted spectral band value. The system then converts the modified spectral signal from the frequency domain to the time domain and transmits the converted modified spectral signal to a server.

Abstract: A method, a device, a computer readable medium and an electronic apparatus for speech signal processing are disclosed. The method comprises: acquiring sound source position information and at least two channels of sound signals from a microphone array; suppressing, according to the sound source position information, a sound signal from the sound source direction in the at least two channels of sound signals, to obtain a noise reference signal of the microphone array; acquiring, according to the sound source position information, a sound signal from the sound source direction in the at least two channels of sound signals, to obtain a speech reference signal; removing, based on the noise reference signal, a residual noise signal in the speech reference signal to obtain a desired speech signal.

Abstract: A method and apparatus that dynamically adjust operational parameters of a text-to-speech engine in a speech-based system are disclosed. A voice engine or other application of a device provides a mechanism to alter the adjustable operational parameters of the text-to-speech engine. In response to one or more environmental conditions, the adjustable operational parameters of the text-to-speech engine are modified to increase the intelligibility of synthesized speech.

Abstract: The application discloses a debugging method for a noise elimination algorithm, an apparatus and an electronic device, which relate to the technical fields of voice, automatic driving and intelligent transportation. An implementation scheme is: when the noise elimination algorithm is debugged, acquiring multiple voice control signals from a vehicle to be debugged, modifying a weight of a configuration parameter of the noise elimination algorithm in a digital signal processing to obtain an updated noise elimination algorithm; then adopting the updated noise elimination algorithm to perform noise elimination processing on the multiple voice control signals; if control results of noise-eliminated voice control signals on the vehicle to be debugged do not meet a preset condition, continuing to modify the weight of the configuration parameter until the preset condition is met, and then sending a noise elimination algorithm that meets the preset condition to the vehicle to be debugged.

Abstract: This voice processing device is provided with: an utterer's position detection unit which specifies, as position microphones of an utterer, microphones that receive a voice signal of WuW on the basis of the characteristics of each voice signal for a prescribed time, when the WuW voice is detected, the voice signal being held in a voice signal buffer unit; and a CTC unit (one example of a voice processing unit) which outputs a voice uttered by the utterer and suppress a voice uttered by an occupant, who is not the utterer, by using the voice signal for the prescribed time, which is held in the voice signal buffer unit, and information relating to the utterer's position microphones.

Abstract: A device includes a memory configured to store instructions and one or more processors configured to execute the instructions. The one or more processors are configured to execute the instructions to receive audio data including a first audio frame corresponding to a first output of a first microphone and a second audio frame corresponding to a second output of a second microphone. The one or more processors are also configured to execute the instructions to provide the audio data to a first noise-suppression network and a second noise-suppression network. The first noise-suppression network is configured to generate a first noise-suppressed audio frame and the second noise-suppression network is configured to generate a second noise-suppressed audio frame. The one or more processors are further configured to execute the instructions to provide the noise-suppressed audio frames to an attention-pooling network. The attention-pooling network is configured to generate an output noise-suppressed audio frame.

Abstract: An audio device for improved talker discrimination is provided. To improve suppression of close talker interference, i.e., of a person talking in close proximity to the user of the audio device, the audio device comprises at least an audio input to receive a voice input signal; a filter bank, configured to provide a plurality of sub-band signals from the voice input signal; a multi-band audio expander, arranged to receive at least a group of the sub-band signals and configured to conduct audio expansion on the group of sub-band signals to provide gain-controlled sub-band signals; and an audio output, configured to provide a voice output signal from at least the gain-controlled sub-band signals.

Abstract: A method for multi-channel voice activity detection includes receiving a sequence of input frames characterizing streaming multi-channel audio captured by an array of microphones. Each channel of the streaming multi-channel audio includes respective audio features captured by a separate dedicated microphone. The method also includes determining, using a location fingerprint model, a location fingerprint indicating a location of a source of the multi-channel audio relative to the user device based on the respective audio features of each channel of the multi-channel audio. The method also includes generating an output from an application-specific classifier. The first score indicates a likelihood that the multi-channel audio corresponds to a particular audio type that the particular application is configured to process.

Abstract: Illustrative embodiments provide a method and system for communicating air traffic control information. An audio signal comprising voice activity is received. Air traffic control information in the voice activity is identified using an artificial intelligence algorithm. A text transcript of the air traffic control information is generated and displayed on a confirmation display. Voice activity in the audio signal may be detected by identifying portions of the audio signal that comprise speech based on a comparison between the power spectrum of the audio signal and the power spectrum of noise and forming speech segments comprising the portions of the audio signal that comprise speech.

Abstract: A device includes a memory configured to store instructions and one or more processors configured execute the instructions. The one or more processors are configured execute the instructions to receive audio data including first audio data corresponding to a first output of a first microphone and second audio data corresponding to a second output of a second microphone. The one or more processors are also configured to execute the instructions to provide the audio data to a dynamic classifier. The dynamic classifier is configured to generate a classification output corresponding to the audio data. The one or more processors are further configured to execute the instructions to determine, at least partially based on the classification output, whether the audio data corresponds to user voice activity.

Abstract: A method for hybrid noise suppression includes receiving a processed audio signal from an audio device. The processed audio signal results from a partial audio processing performed on a noisy audio input signal. The method further includes predicting a noise suppression parameter using a neural network model operating on the processed audio signal and generating a noise-suppressed audio signal from the processed audio signal, using the noise suppression parameter. The method further includes generating a noise-suppressed audio output signal from the noise-suppressed audio signal using an additional audio processing and outputting the noise-suppressed audio output signal.

Abstract: Embodiments of this application disclose a bandwidth extension (BWE) method and apparatus. The method is performed by an electronic device, and includes: performing a time-frequency transform on a to-be-processed narrowband signal to obtain a corresponding initial low-frequency spectrum; obtaining a correlation parameter of a high-frequency portion and a low-frequency portion of a target broadband spectrum based on the initial low-frequency spectrum by using a neural network model; obtaining an initial high-frequency spectrum based on the correlation parameter and the initial low-frequency spectrum; and obtaining a broadband signal according to a target low-frequency spectrum and a target high-frequency spectrum.

Abstract: A sensor device transmits, to an external device installed external to the sensor device, sensing data generated from monitoring a target, and includes a sensor unit that generates sensing data including background noise data. The background noise data represents noise from a cause other than the target. The sensor device further includes an extraction unit that extracts the background noise data from the sensing data, and a transmission unit that transmits the background noise data extracted by the extraction unit to the external device.

Abstract: An audio processing apparatus includes a preprocessor which extracts a voice-band signal from a first electric signal, and outputs a first output signal containing the voice-band signal; a first controller which generates a first amplification coefficient for multiplying with the first output signal to compress a dynamic range of an intensity of the first output signal, and generates a first modified amplification coefficient by smoothing the first amplification coefficient with a first time constant; and a first multiplier which multiplies the first modified amplification coefficient and the first output signal. The first time constant is a first rise time constant when the intensity increases, and is a first decay time constant when the intensity decreases. The first rise time constant is not less than a temporal resolution of hearing of a hearing-impaired person, and is less than a duration time of sound which induces recruitment in the hearing-impaired person.

Abstract: A sound processing method includes: determining a vector of a first residual signal according to a first signal vector and a second signal vector, the first signal vector including a first voice signal and a first noise signal input into the first microphone, the second signal vector including a second voice signal and a second noise signal input into the second microphone, and the first residual signal including the second noise signal and a residual voice signal; determining a gain function of a current frame according to the vector of the first residual signal and the first signal vector; and determining a first voice signal of the current frame according to the first signal vector and the gain function of the current frame.

Abstract: A voice quality estimation apparatus includes: a packet sequence creation unit configured to create a first sequence by applying a first characteristic indicating that quality degradation caused by packet loss is perceived by a user all at once, to a sequence consisting of elements each indicating whether or not a packet of a voice call has been lost; a smoothing unit configured to create a second sequence from the first sequence; a degradation amount emphasis unit configured to create a third sequence from the second sequence; a packet loss tolerance characteristics reflection unit configured to create a fourth sequence from the third sequence; a degradation amount calculation unit configured to calculate a degradation amount from the fourth sequence; and a listening quality estimation unit configured to estimate voice quality that is to be experienced by the user, from the degradation amount.

Abstract: A method for automatically detecting audio feedback in an input audio signal includes separately filtering the audio input signal with a plurality of separate analysis audio filters to generate a plurality of filtered audio signals. The separate analysis audio filters are different. Then, comparing at least two of the filtered audio signals to obtain an energy level difference. Performing one or more repetitions of the steps of filtering and comparing to establish a plurality of the energy level differences. Then comparing energy level differences from at least two of the repetitions to detect the audio feedback. The method includes features of automatically performing audio feedback suppression of the detected audio feedback.

Abstract: A video system and method are presented that uses an output-receiving microphone mounted on the housing of the video system to receive a signal representative of the output of a speaker in a use-environment. This signal is compared with a second signal received from a spoken-word microphone that is mounted more remotely from the speaker. In some embodiments, the spoken-word microphone is positioned in a low-pass filter tune pipe and is combined with a separate spoken-word microphone in a tuned microphone array so as to filter out frequencies not associated with the human voice. The two signals are magnitude matched, and the first signal is subtracted from the second to generate an improved voice signal for a voice recognition system.

Abstract: An audio data processing method is provided. The method includes: obtaining multi-path audio data in an environmental space, obtaining a speech data set based on the multi-path audio data, and separately generating, in a plurality of enhancement directions, enhanced speech information corresponding to the speech data set; matching a speech hidden feature in the enhanced speech information with a target matching word, and determining an enhancement direction corresponding to the enhanced speech information having a highest degree of matching with the target matching word as a target audio direction; obtaining speech spectrum features in the enhanced speech information, and obtaining, from the speech spectrum features, a speech spectrum feature in the target audio direction; and performing speech authentication on the speech hidden feature and the speech spectrum feature that are in the target audio direction based on the target matching word, to obtain a target authentication result.

Abstract: There is provided mechanisms for frame loss concealment. A method is performed by a receiving entity. The method comprises adding, in association with constructing a substitution frame for a lost frame, a noise component to the substitution frame. The noise component has a frequency characteristic corresponding to a low-resolution spectral representation of a signal in a previously received frame.

Abstract: An audio device for improved talker discrimination is provided. To improve suppression of close talker interference, the audio device comprises at least a first and a second audio input to receive a first and second voice input signal; a first filter bank, configured to provide a plurality of first sub-band signals; a second filter bank, configured to provide a plurality of second sub-band signals; a correlator, configured to determine at least one signal correlation between at least a group of the first sub-band signals and at least a group of the second sub-band signals; and an attenuator, arranged to receive at least the group of the first sub-band signals and configured to conduct signal attenuation on the group of the first sub-band signals to provide gain-controlled sub-band signals, wherein the signal attenuation is based on the determined at least one signal correlation.

Abstract: A method, an apparatus, and logic to post-process raw gains determined by input processing to generate post-processed gains, comprising using one or both of delta gain smoothing and decision-directed gain smoothing. The delta gain smoothing comprises applying a smoothing filter to the raw gain with a smoothing factor that depends on the gain delta: the absolute value of the difference between the raw gain for the current frame and the post-processed gain for a previous frame. The decision-directed gain smoothing comprises converting the raw gain to a signal-to-noise ratio, applying a smoothing filter with a smoothing factor to the signal-to-noise ratio to calculate a smoothed signal-to-noise ratio, and converting the smoothed signal-to-noise ratio to determine the second smoothed gain, with smoothing factor possibly dependent on the gain delta.

Abstract: A coding method and a decoding method are provided which can use in combination a predictive coding and decoding method which is a coding and decoding method that can accurately express coefficients which are convertible into linear prediction coefficients with a small code amount and a coding and decoding method that can obtain correctly, by decoding, coefficients which are convertible into linear prediction coefficients of the present frame if a linear prediction coefficient code of the present frame is correctly input to a decoding device.

Abstract: Systems and methods are disclosed for providing voice and noise activity detection with audio automixers that can reject errant non-voice or non-human noises while maximizing signal-to-noise ratio and minimizing audio latency.

Abstract: Audio systems, methods, and processor instructions are provided that detect voice activity of a user and provide an output voice signal. The systems, methods, and instructions receive a plurality of microphone signals and combine the plurality of microphone signals according to a first combination and a second combination. The first combination produces a primary signal having enhanced response in the direction of the user's mouth, and the second combination produces a reference signal having reduced response in the direction of the user's mouth. The primary signal and the reference signal are added and subtracted to produce a voice-enhanced signal and a voice-reduced signal, respectively. The voice-enhanced signal and the voice-reduced signal are compares and an output voice signal is provided based upon the comparison.

Abstract: An ambient-aware audio system reduces stationary noise and maintains dynamic environmental sound in a received input audio signal. The system includes a signal-to-noise ratio (SNR) estimator that estimates an a priori SNR and an a posteriori SNR, a gain function that uses the estimated SNRs as inputs to compute coefficients of a frequency domain noise reduction filter that uses the computed coefficients to filter a frame of the input audio signal to generate an output audio signal. The SNR estimator, gain function, and filter are configured to iterate over a plurality of frames of the input audio signal. The SNRs are estimated using the input audio signal and the output audio signal associated with one or more of the plurality of frames. The gain function is derived to minimize an expected value of differences between spectral amplitudes of the output audio signal and the input audio signal.

Abstract: A hearing device includes: an input module for provision of a first input signal; a processor configured to provide an electrical output signal based on the first input signal; a receiver configured to provide an audio output signal; and a controller comprising a speech intelligibility estimator configured to determine a speech intelligibility indicator indicative of speech intelligibility based on the first input signal, wherein the controller is configured to control the processor based on the speech intelligibility indicator; wherein the speech intelligibility estimator comprises a decomposition module configured to decompose the first input signal into a first representation of the first input signal in a frequency domain, wherein the first representation comprises one or more elements representative of the first input signal; and wherein the decomposition module comprises one or more characterization blocks for characterizing the one or more elements of the first representation in the frequency domain.

Abstract: A method for encoding multiple descriptions for a media stream includes: determining, for a current block of the media stream, a first number of duplicate blocks, determining, for the current block, a plurality of complementary forward gain factors, and determining a first number of descriptions for the current block by applying the plurality of complementary forward gain factors to the first number of duplicate blocks. A method for decoding multiple descriptions for a media stream includes: determining, for a current block of the media stream, a first number of descriptions from the media stream, in which each description comprises a scaled block corresponding to the current block, determining backward gain factors for the first number of scaled blocks, and determining the current block by applying the backward gain factors to the first number of scaled blocks.