Abstract: A multifunction simultaneous interpretation device includes an audio input and recognition module for receiving input speech of a first language, recognizing same, and converting the input speech of the first language into input speech signals of the first language; an interpretation module electrically connected to the audio input and recognition module and configured to receive the input speech signals of the first language, interpret and convert same into speech signals of a second language different from the first language, and make the speech signals of the second language as output; an output module electrically connected to the interpretation module and configured to receive the speech signals of the second language from the interpretation module and output a voice representing the speech signals of the second language; and a wireless transceiver electrically connected to the interpretation module and configured for wireless signal transmission to a mobile phone.

Abstract: A speech processing apparatus includes a specifier, a determiner, and a modulator. The specifier specifies an emphasis part of speech to be output. The determiner determines, from among a plurality of output units, a first output unit and a second output unit for outputting speech for emphasizing the emphasis part. The modulator modulates the emphasis part of at least one of first speech to be output to the first output unit and second speech to be output to the second output unit such that at least one of a pitch and a phase is different between the emphasis part of the first speech and the emphasis part of the second speech.

Abstract: A system senses audio, imagery, and/or other stimulus from a user's environment, and responds to fulfill user desires. In one particular arrangement, a discovery session is launched when the user speaks a cueing expression, which serves to switch the system from a lower activity state to a heightened alert state. The system may recognize that the speech expresses a user request that requires analysis of camera-captured imagery to fulfill. In response the system can apply an operation, such as a recognition operation (e.g., barcode decoding), to the imagery and take an action based on resulting information. Operation of the system can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.

Abstract: A speech recognition method and an apparatus which recognize speech, based on speaker recognition, and output a result of the speech recognition are provided. The speech recognition method includes activating a session for receiving an input of an audio signal, performing speech recognition on a speech signal detected from the input audio signal while the session is maintained, determining whether a speaker of the speech signal is a registered speaker based on speaker information generated from the speech signal, determining whether to maintain the session based on a result of the determination, and outputting a result of performing the speech recognition.

Abstract: A translation method includes: selecting a source word from a source sentence; generating mapping information including location information of the selected source word mapped to the selected source word in the source sentence; and correcting a target word, which is generated by translating the source sentence, based on location information of a feature value of the target word and the mapping information.

Abstract: A system or method for aligning in time a first transcript to audio data used to create the first transcript. The system or method performs the following actions. Receiving the first transcript. The first transcript includes a first plurality of words that are in the audio data. Transcribing the audio data to make a second transcript. The second transcript includes a second plurality of words that are in the audio data and a respective time of a location in the audio data of each word of the second plurality. For each word of the second plurality found in the first plurality, assigning the respective time of the location of the word of the second plurality to the word of the first plurality thereby aligning in time the first transcript to the audio data.

Abstract: The exemplary embodiments described herein are related to techniques for automatically generating narratives about data based on communication goal data structures that are associated with configurable content blocks. The use of such communication goal data structures facilitates modes of operation whereby narratives can be generated in real-time and/or interactive manners.

Abstract: Example embodiments are disclosed where a narrative generation platform is integrated with a conversational interface such as a Chatbot to support interactive and dynamic narrative generation in response to speech inputs from users. Such a system can be further integrated with a visualization platform to allow the speech input through the conversational interface to interactively and dynamically focus and control visualizations and/or narratives that accompany the visualizations.

Abstract: A configuration provides quality control compliance for a plurality of machine language interpreters. A processor receives a plurality of requests for human-spoken language interpretation from a first human-spoken language to a second human-spoken language. Further, processor routes the plurality of requests to a plurality of machine language interpreters. In addition, an artificial intelligence system associated the plurality of machine language interpreters determines one or more quality control criteria. The processor also monitors compliance of the one or more quality control criteria by the plurality of machine language interpreters during simultaneously occurring machine language interpretations performed by the machine language interpreters.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating network outputs using insertion operations.

Abstract: The present disclosure describes systems and methods of fraud protection. A listening device may monitor ambient sound and detect one or more triggering sound patterns. The listening device may record the one or more triggering sound patterns and record a person's voice, and send the recordings to a server, wherein the server is configured to calculate a confidence level of fraud based on the one or more triggering sound patterns and the recording of the person's voice using a speech pattern model of the person, and to output an alert if the confidence level of fraud is greater than a threshold value.

Abstract: A speech synthesis apparatus includes a content selection unit that selects a text content item to be converted into speech; a related information selection unit that selects related information which can be at least converted into text and which is related to the text content item selected by the content selection unit; a data addition unit that converts the related information selected by the related information selection unit into text and adds text data of the text to text data of the text content item selected by the content selection unit; a text-to-speech conversion unit that converts the text data supplied from the data addition unit into a speech signal; and a speech output unit that outputs the speech signal supplied from the text-to-speech conversion unit.

Abstract: Systems and methods for establishing a communications system between multiple electronic devices are described herein. In some embodiments, first audio data representing a first utterance may be received from an initiating device. A first user account associated with the initiating device may be determined. After determining that the utterance comprises an intent to communicate with a target, a list of entity names associated with the user account may be generated. Each entity name may represent a user contact associated with the first user account, a user device corresponding to the first user account, and/or a set of entity names representing user contacts and devices. Based on a relative comparison of each entity name to the target's name, an entity name may be selected from the plurality of entity names. A communications session may then be established between the initiating device and a device represented by the selected entity name.

Abstract: The present technology relates to a decoding apparatus, a decoding method and a program which make it possible to obtain sound with higher quality. A demultiplexing circuit demultiplexes an input code string into a gain code string and a signal code string. A signal decoding circuit decodes the signal code string to output a time series signal. A gain decoding circuit decodes the gain code string. That is, the gain decoding circuit reads out gain values and gain inclination values at predetermined gain sample positions of the time series signal and interpolation mode information. An interpolation processing unit obtains a gain value at each sample position between two gain sample positions through linear interpolation or non-linear interpolation according to the interpolation mode based on the gain values and the gain inclination values. A gain applying circuit adjusts a gain of the time series signal based on the gain values. The present technology can be applied to a decoding apparatus.

Abstract: A method and associated system for recognizing speech using multiple speech recognition algorithms. The method includes receiving speech at a microphone installed in a vehicle, and determining results for the speech using a first algorithm, e.g., embedded locally at the vehicle. Speech results may also be received at the vehicle for the speech determined using a second algorithm, e.g., as determined by a remote facility. The results for both may include a determined speech topic and a determined speech slotted value, along with corresponding confidence levels for each. The method may further include using at least one of the determined first speech topic and the received second speech topic to determine the topic associated with the received speech, even when the first speech topic confidence level of the first speech topic, and the second speech topic confidence level of the second speech topic are both a low confidence level.

Abstract: Methods and systems are provided for improving speech recognition of multilingual named entities. In some embodiments, a list comprising a plurality of named entities may be accessed by a computing device. A first named entity represented in the native language may be compared with the first named entity represented in the foreign language. One or more words that appear in both the first named entity represented in the native language and the first named entity represented in the foreign language may be identified as one or more foreign words. A grapheme-to-phoneme (G2P) conversion may be applied to the one or more foreign words, wherein graphemes of the one or more foreign words are mapped to phonemes in the native language. The G2P conversion may result in a native pronunciation for each of the one or more foreign words, which are added to a recognition dictionary along with the native pronunciations.

Abstract: A device that determines an echo latency estimate by subsampling reference audio data. The device may determine the echo latency corresponding to an amount of time between sending reference audio data to loudspeaker(s) and microphone audio data corresponding to the reference audio data being received. The device may generate subsampled reference audio data by selecting only portions of the reference audio data that have a magnitude above a desired percentile. For example, the device may compare a magnitude of an individual reference audio sample to a percentile estimate value and sample only the reference audio samples that exceed the percentile estimate value. The device generate cross-correlation data between the subsampled reference audio data and the microphone audio data and may estimate the echo latency based on an earliest significant peak represented in the cross-correlation data.

Abstract: A method of translating a first language-based speech signal into a second language is provided. The method includes receiving the first language-based speech signal, converting the first language-based speech signal into a first language-based text including non-verbal information, by performing voice recognition on the first language-based speech signal, and translating the first language-based text into the second language, based on the non-verbal information.

Abstract: A mobile terminal is provided. The mobile terminal includes a voice receiving module configured to receive the voice of a user through a first application and to generate first voice data for the voice received through the first application, a control module configured to transmit the first voice data and user information corresponding to the first voice data to a service server and to request the service server to register the first voice data and the user information, and a communication module configured to transmit, to the service server, a request for the user information corresponding to the voice of the user received through a second application when the voice of the user is received through the second application.

Abstract: Methods and systems for determining an intent of an utterance using contextual information associated with a requesting device are described herein. Voice activated electronic devices may, in some embodiments, be capable of displaying content using a display screen. Entity data representing the content rendered by the display screen may describe entities having similar attributes as an identified intent from natural language understanding processing. Natural language understanding processing may attempt to resolve one or more declared slots for a particular intent and may generate an initial list of intent hypotheses ranked to indicate which are most likely to correspond to the utterance. The entity data may be compared with the declared slots for the intent hypotheses, and the list of intent hypothesis may be re-ranked to account for matching slots from the contextual metadata. The top ranked intent hypothesis after re-ranking may then be selected as the utterance's intent.