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  2. Deep learning speech synthesis - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_speech_synthesis

    In June 2018, Google proposed to use pre-trained speaker verification models as speaker encoders to extract speaker embeddings. [14] The speaker encoders then become part of the neural text-to-speech models, so that it can determine the style and characteristics of the output speech.

  3. Speech coding - Wikipedia

    en.wikipedia.org/wiki/Speech_coding

    Speech coding is an application of data compression to digital audio signals containing speech.Speech coding uses speech-specific parameter estimation using audio signal processing techniques to model the speech signal, combined with generic data compression algorithms to represent the resulting modeled parameters in a compact bitstream.

  4. Speech recognition - Wikipedia

    en.wikipedia.org/wiki/Speech_recognition

    The use of speech recognition is more naturally suited to the generation of narrative text, as part of a radiology/pathology interpretation, progress note or discharge summary: the ergonomic gains of using speech recognition to enter structured discrete data (e.g., numeric values or codes from a list or a controlled vocabulary) are relatively ...

  5. Linear predictive coding - Wikipedia

    en.wikipedia.org/wiki/Linear_predictive_coding

    Linear predictive coding (LPC) is a method used mostly in audio signal processing and speech processing for representing the spectral envelope of a digital signal of speech in compressed form, using the information of a linear predictive model. [1] [2] LPC is the most widely used method in speech coding and speech synthesis.

  6. Speaker recognition - Wikipedia

    en.wikipedia.org/wiki/Speaker_recognition

    It was developed by voice recognition company Nuance (that in 2011 acquired the company Loquendo, the spin-off from CSELT itself for speech technology), the company behind Apple's Siri technology. 93% of customers gave the system at "9 out of 10" for speed, ease of use and security. [18] Speaker recognition may also be used in criminal ...

  7. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    Around 2006, bidirectional LSTM started to revolutionize speech recognition, outperforming traditional models in certain speech applications. [ 38 ] [ 39 ] They also improved large-vocabulary speech recognition [ 3 ] [ 4 ] and text-to-speech synthesis [ 40 ] and was used in Google voice search , and dictation on Android devices . [ 41 ]

  8. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Seq2seq RNN encoder-decoder with attention mechanism, training Seq2seq RNN encoder-decoder with attention mechanism, training and inferring The attention mechanism is an enhancement introduced by Bahdanau et al. in 2014 to address limitations in the basic Seq2Seq architecture where a longer input sequence results in the hidden state output of ...

  9. List of speech recognition software - Wikipedia

    en.wikipedia.org/wiki/List_of_speech_recognition...

    Speech Recognition is available only in English, French, Spanish, German, Japanese, Simplified Chinese, and Traditional Chinese and only in the corresponding version of Windows; meaning you cannot use the speech recognition engine in one language if you use a version of Windows in another language.