A method for voice modification during a telephone call comprising receiving a source audio signal associated with at least one participant, wherein the source audio signal comprises a voice of the at least one participant, detecting a source dialect of the at least one participant, selecting a target dialect based on at least a characteristic of a target participant and creating a modulated audio signal based on the source audio signal, the source dialect, and the target dialect and transmitting the modulated audio signal to the target participant.

An apparatus for processing an audio signal and method thereof are disclosed. The present invention includes receiving, by an audio processing apparatus, an audio signal including a first data of a first block encoded with rectangular coding scheme and a second data of a second block encoded with non-rectangular coding scheme; receiving a compensation signal corresponding to the second block; estimating a prediction of an aliasing part using the first data; and, obtaining a reconstructed signal for the second block based on the second data, the compensation signal and the prediction of aliasing part.

A quantization device includes: a trellis-structured vector quantizer which quantizes a first error vector between an N-dimensional (here, “N” is two or more) subvector and a first predictive vector; and an inter-frame predictor which generates a first predictive vector from the quantized N-dimensional subvector, wherein the inter-frame predictor uses a predictive coefficient comprising an N×N matrix and performs an inter-frame prediction using the quantized N-dimensional subvector of a previous stage.

An estimation device includes a memory, and processing circuitry coupled to the memory and configured to receive an input of an input audio signal that is an audio signal in which sounds from a plurality of sound sources are mixed, and an input of supplemental information, and output an estimation result of mask information that identifies a mask for extracting a sound of any one of the sound sources included in an entire or a part of a signal included in the input audio signal, the signal being identified by the supplemental information, cause a neural network to iterate a process of outputting the estimation result of the mask information, and cause the neural network to output an estimation result of the mask information for a different sound source, by inputting a different piece of the supplemental information to the neural network at each iteration.

Despite many practical limitations imposed by mobile device platforms and application execution environments, vocal musical performances may be captured and continuously pitch-corrected for mixing and rendering with backing tracks in ways that create compelling user experiences. Based on the techniques described herein, even mere amateurs are encouraged to share with friends and family or to collaborate and contribute vocal performances as part of virtual “glee clubs.” In some implementations, these interactions are facilitated through social network- and/or eMail-mediated sharing of performances and invitations to join in a group performance. Using uploaded vocals captured at clients such as a mobile device, a content server (or service) can mediate such virtual glee clubs by manipulating and mixing the uploaded vocal performances of multiple contributing vocalists.

A processing buffer unit stores an audio signal. A pitch calculation unit and a pitch cycle correction unit calculate a multiple of N as the number of samples in a pitch cycle of the audio signal, in which N is an integer equal to or more than 1. A processing control unit and a start-position movement amount correction unit sequentially determine, as a sample in a start position of a compression process in a time axis domain of the audio signal, a (multiple of N)-th sample from a start position immediately before the start position. An operation unit compresses samples in a predetermined number times the pitch cycle from the sample in the start position in a time axis domain, and sets the number of samples after the compression to be the multiple of N. The present technology, for example, may be applied to an audio signal processing apparatus.

A speech recognition system uses, in one embodiment, an extended phonetic dictionary that is obtained by processing words in a user's set of databases, such as a user's contacts database, with a set of pronunciation guessers. The speech recognition system can use a conventional phonetic dictionary and the extended phonetic dictionary to recognize speech inputs that are user requests to use the contacts database, for example, to make a phone call, etc. The extended phonetic dictionary can be updated in response to changes in the contacts database, and the set of pronunciation guessers can include pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser.

Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

A method for controlling an operation of a target device using a plurality of input devices is disclosed. The method comprises: receiving from one of the plurality of the input devices a first operation instruction issued to the target device, with a first data format; recognizing the first operation instruction and the first data format; determining that the one of the plurality of the input devices is a first input device corresponding to the first data format; and providing to a user of the target device a recommendation for a second input device, a type of the second input device being different from a type of the first input device, when it is determined that a type of the first operation instruction is identical to a type of a second operation instruction received from the second input device earlier than the reception of the first operation instruction.

The embodiments of the present invention relates to a voice activity detector and a method thereof. The voice activity detector is configured to detect voice activity in a received input signal comprising an input section configured to receive a signal from a primary voice detector of said VAD indicative of a primary VAD decision and at least one signal from at least one external VAD indicative of a voice activity decision from the at least one external VAD, a processor configured to combine the voice activity decisions indicated in the received signals to generate a modified primary VAD decision, and an output section configured to send the modified primary VAD decision to a hangover addition unit of said VAD.