Showing 5 open source projects for "text aligner"

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  • 1
    StyleTTS 2

    StyleTTS 2

    Towards Human-Level Text-to-Speech through Style Diffusion

    ...StyleTTS2 supports both single-speaker and multi-speaker configurations, with the ability to sample or transfer styles from reference audio, making it powerful for expressive TTS and character voices. The repository includes training scripts, configuration files, and pre-trained auxiliary modules such as a text aligner, pitch extractor, and PL-BERT-based linguistic encoder.
    Downloads: 0 This Week
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  • 2
    Transformer TTS

    Transformer TTS

    Implementation of a Transformer based neural network

    TransformerTTS is an implementation of a non-autoregressive Transformer-based neural network for text-to-speech, built with TensorFlow 2. It takes inspiration from architectures like FastSpeech, FastSpeech 2, FastPitch, and Transformer TTS, and extends them with its own aligner and forward models. The system separates alignment learning and acoustic modeling: an autoregressive Transformer is used as an aligner to extract phoneme-to-frame durations, while a non-autoregressive “ForwardTransformer” generates mel-spectrograms conditioned on text and durations. ...
    Downloads: 0 This Week
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  • 3
    Sanchay
    Sanchay is a collection of tools and APIs for language researchers. It has some implementations of NLP algorithms, some flexible APIs, several user friendly annotation interfaces and Sanchay Query Language for language resources.
    Downloads: 1 This Week
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  • 4
    A Java port of LDC's Champollion sentence aligner (http://champollion.sourceforge.net). Intended audience is Natural Language researchers wishing to sentence-align parallel text. In the future, Akerblad will extend Champollion with such features as rule
    Downloads: 0 This Week
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  • 5
    mms-300m-1130-forced-aligner

    mms-300m-1130-forced-aligner

    CTC-based forced aligner for audio-text in 158 languages

    mms-300m-1130-forced-aligner is a multilingual forced alignment model based on Meta’s MMS-300M wav2vec2 checkpoint, adapted for Hugging Face’s Transformers library. It supports forced alignment between audio and corresponding text across 158 languages, offering broad multilingual coverage. The model enables accurate word- or phoneme-level timestamping using Connectionist Temporal Classification (CTC) emissions.
    Downloads: 0 This Week
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