Amazon Technologies, Inc.

Viacheslav Klimkov

Thomas Edward Merritt

Thomas Renaud Drugman

Srikanth Ronanki

Andrew Paul Breen

Jaime Lorenzo Trueba

Roberto Barra-Chicote

Roberto Barra Chicote

Adam Franciszek Nadolski

Javier Latorre

Alexander Galkin

Michal Czuczman

You Wang

Masaki Noguchi

During text-to-speech processing, a speech model creates output audio data, including speech, that corresponds to input text data that includes a representation of the speech. A spectrogram estimator estimates a frequency spectrogram of the speech; the corresponding frequency-spectrogram data is used to condition the speech model. A plurality of acoustic features corresponding to different segments of the input text data, such as phonemes, syllable-level features, and/or word-level features, may be separately encoded into context vectors; the spectrogram estimator uses these separate context vectors to create the frequency spectrogram.

Text-to-speech (TTS) processing

A speech-processing system receives input data representing text. An encoder processes segments of the text to determine embedding data, and a decoder processes the embedding data to determine one or more categories associated with each segment. Output data is determined by selecting words based on the segments and categories.

Synthetic speech processing

A text-to-speech (TTS) system that is capable of considering characteristics of various portions of text data in order to create continuity between segments of synthesized speech. The system can analyze text portions of a work and create feature vectors including data corresponding to characteristics of the individual portions and/or the overall work. A TTS processing component can then consider feature vector(s) from other portions when performing TTS processing on text of a first portion, thus giving the TTS component some intelligence regarding other portions of the work, which can then result in more continuity between synthesized speech segments.

Contextual text-to-speech processing

Audio data from a first, source speaker is received and processed to determine linguistic units and vocal characteristics corresponding to those linguistic units. The linguistic units may either be determined from received text data or may be determined from the audio data using automatic speech recognition. A model is trained using training data from a second, target speaker. The trained model concatenates the linguistic units with the vocal characteristics to produce output speech that has the 'voice' of the target speaker and the vocal characteristics of the source speaker.

Text-to-speech (TTS) processing with transfer of vocal characteristics

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Gdansk, Poland

Viacheslav Klimkov