Showing 7 open source projects for "text processing"

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  • 1
    Whisper

    Whisper

    Robust Speech Recognition via Large-Scale Weak Supervision

    OpenAI Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. These tasks are jointly represented...
    Downloads: 61 This Week
    Last Update:
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  • 2
    Handy STT

    Handy STT

    A free, open source, and extensible speech-to-text application

    Handy is a free, open-source, offline speech-to-text application built for privacy, accessibility, and extensibility. Developed using Tauri (Rust + React/TypeScript), it runs natively across Windows, macOS, and Linux while performing local speech recognition without sending any audio to cloud servers. Handy allows users to start transcription instantly using a configurable keyboard shortcut—press to record, release to transcribe—and automatically pastes the resulting text into any active...
    Downloads: 28 This Week
    Last Update:
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  • 3
    WhisperX

    WhisperX

    Automatic Speech Recognition with Word-level Timestamps

    WhisperX is an advanced speech recognition system built on top of OpenAI’s Whisper model, designed to improve transcription accuracy and timing precision for long-form audio. It addresses key limitations of standard Whisper implementations by introducing voice activity detection and forced alignment techniques to produce word-level timestamps. The system enables batched inference, significantly increasing transcription speed while maintaining high accuracy. It is particularly effective for...
    Downloads: 21 This Week
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  • 4
    Insanely Fast Whisper

    Insanely Fast Whisper

    An opinionated CLI to transcribe Audio files w/ Whisper on-device

    Insanely Fast Whisper is a high-performance command-line tool designed to dramatically accelerate speech-to-text transcription using OpenAI’s Whisper models on local hardware. It leverages modern optimizations such as batch processing, mixed precision, and advanced attention mechanisms like Flash Attention to significantly reduce inference time while maintaining high transcription accuracy. The project is built on top of the Transformers ecosystem and integrates with libraries such as Optimum to maximize GPU efficiency. ...
    Downloads: 2 This Week
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  • 5
    Faster Whisper

    Faster Whisper

    Faster Whisper transcription with CTranslate2

    Faster Whisper is an optimized implementation of the Whisper speech recognition model designed to deliver significantly faster inference while maintaining comparable accuracy. It leverages efficient inference engines and optimized computation strategies to reduce latency and resource consumption. The system is particularly useful for real-time or large-scale transcription tasks where performance is critical. It supports multiple model sizes, allowing users to balance speed and accuracy based...
    Downloads: 28 This Week
    Last Update:
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  • 6
    Speechalyzer

    Speechalyzer

    Process large speech data wrt transcription, labeling and annotation

    ...It is implemented as a client server based framework in Java and interfaces software for speech recognition, synthesis, speech classification and quality evaluation. The application is mainly the processing of training data for speech recognition and classification models and performing benchmarking tests on speech-to-text, text-to-speech and speech classification software systems.
    Downloads: 0 This Week
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  • 7

    Speech Sentiment Analysis

    Voice to Text Sentiment Analysis

    Voice to text Sentiment analysis converts the audio signal to text to calculate appropriate sentiment polarity of the sentence. The code currently works on one sentence at a time. Sentiment scoring is done on the spot using a speaker. The Speech to text processing system currently being used is the MS Windows speech to text converter. However significant modifications can be made for audio recognition by a refined signal processing system. ...
    Downloads: 0 This Week
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