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Natural Voices Text-to-Speech,
Natural Voices is AT&T's state-of-the-art text-to-speech product, taking text and producing natural-sounding, synthesized speech in a variety of voices and languages.
AT&T WATSON Speech Technologies,
AT&T WATSON integrates several speech technologies, including automatic speech recognition. Tools allow for tuning recognition, adapting language and acoustic models, and adding custom extensions.
System and method for blending synthetic voices,
November 18, 2008
A system and method for generating a synthetic text-to-speech TTS voice are disclosed. A user is presented with at least one TTS voice and at least one voice characteristic. A new synthetic TTS voice is generated by blending a plurality of existing TTS voices according to the selected voice characteristics. The blending of voices involves interpolating segmented parameters of each TTS voice. Segmented parameters may be, for example, prosodic characteristics of the speech such as pitch, volume, phone durations, accents, stress, mis-pronunciations and emotion.
Coarticulation method for audio-visual text-to-speech synthesis,
June 24, 2008
A method for generating animated sequences of talking heads in text-to-speech applications wherein a processor samples a plurality of frames comprising image samples. The processor reads first data comprising one or more parameters associated with noise-producing orifice images of sequences of at least three concatenated phonemes which correspond to an input stimulus. The processor reads, based on the first data, second data comprising images of a noise-producing entity. The processor generates an animated sequence of the noise-producing entity.
Audio-visual selection process for the synthesis of photo-realistic talking-head animations,
November 25, 2003
A system and method for generating photo-realistic talking-head animation from a text input utilizes an audio-visual unit selection process. The lip-synchronization is obtained by optimally selecting and concatenating variable-length video units of the mouth area. The unit selection process utilizes the acoustic data to determine the target costs for the candidate images and utilizes the visual data to determine the concatenation costs. The image database is prepared in a hierarchical fashion, including high-level features (such as a full 3D modeling of the head, geometric size and position of elements) and pixel-based, low-level features (such as a PCA-based metric for labeling the various feature bitmaps).
Automatic Detection Of Non-Stationarity In Speech Signals,
March 18, 2003
When necessary to time scale a speech signal, it is advantageous to do it under influence of a signal that measures the small-window non-stationarity of the speech signal. Three measures of stationarity are disclosed: one that is based on time domain analysis, one that is based on frequency domain analysis, and one that is based on both time and frequency domain analysis.
Signal dependent speech modifications,
November 27, 2001
Speech signals, and similar one-dimensional signals, are time scaled, interpolated, and/or smoothed, when necessary, under influence of a signal that is sensitive to a small window stationarity of the signal that is being modified. Three measures of stationarity are disclosed: one that is based on time domain analysis, one that is based on frequency domain analysis, and one that is based on both time and frequency domain analysis.
Coarticulation method for audio-visual text-to-speech synthesis,
December 9, 2003
A method for generating animated sequences of talking heads in text-to-speech applications wherein a processor samples a plurality of frames comprising image samples. Representative parameters are extracted from the image samples and stored in an animation library. The processor also samples a plurality of multiphones comprising images together with their associated sounds. The processor extracts parameters from these images comprising data characterizing mouth shapes, maps, rules, or equations, and stores the resulting parameters and sound information in a coarticulation library. The animated sequence begins with the processor considering an input phoneme sequence, recalling from the coarticulation library parameters associated with that sequence, and selecting appropriate image samples from the animation library based on that sequence. The image samples are concatenated together, and the corresponding sound is output, to form the animated synthesis.
Synthesis-based pre-selection of suitable units for concatenative speech,
March 14, 2006
A method for generating concatenative speech uses a speech synthesis input to populate a triphone-indexed database that is later used for searching and retrieval to create a phoneme string acceptable for a text-to-speech operation. Prior to initiating the real time synthesis process, a database is created of all possible triphone contexts by inputting a continuous stream of speech. The speech data is then analyzed to identify all possible triphone sequences in the stream, and the various units chosen for each context. During a later text-to-speech operation, the triphone contexts in the text are identified and the triphone-indexed phonemes in the database are searched to retrieve the best-matched candidates.
Coarticulation method for audio-visual text-to-speech synthesis,
October 3, 2006
A method for generating animated sequences of talking heads in text-to-speech applications wherein a processor samples a plurality of frames comprising image samples. Representative parameters are extracted from the image samples and stored in an animation library. The processor also samples a plurality of multiphones comprising images together with their associated sounds. The processor extracts parameters from these images comprising data characterizing mouth shapes, maps, rules, or equations, and stores the resulting parameters and sound information in a coarticulation library. The animated sequence begins with the processor considering an input phoneme sequence, recalling from the coarticulation library parameters associated with that sequence, and selecting appropriate image samples from the animation library based on that sequence. The image samples are concatenated together, and the corresponding sound is output, to form the animated synthesis.
IEEE Fellow, 2002.
For contributions to text-to-speech synthesis technology
Science & Technology Medal, 2001.
Honored for significant contributions to the creation and development of a text-to-speech (TTS) synthesis system.