Search Results for "diarization"
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Showing 9 open source projects for "diarization"
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1
WhisperX
Automatic Speech Recognition with Word-level Timestamps
...It is particularly effective for long recordings, where traditional approaches may suffer from drift, repetition, or misalignment. whisperx also supports speaker diarization, allowing identification of different speakers within a conversation. Its architecture combines multiple components to enhance both performance and usability in real-world transcription tasks. Overall, whisperx provides a more robust and scalable solution for high-quality speech-to-text applications. -
2
AutoSubs
Instantly generate AI-powered subtitles on your device
...It supports both standalone usage and integration with professional video editing software such as DaVinci Resolve, allowing creators to generate and edit subtitles within their existing workflows. The tool leverages speech-to-text models, including OpenAI Whisper, to produce high-quality transcriptions and can differentiate between speakers using diarization techniques. Users can customize subtitle styling, adjust timing, and export results in multiple formats, making it suitable for content creators, filmmakers, and editors. AutoSubs is designed with performance in mind, offering efficient processing through a Rust-based backend and supporting multiple operating systems including Windows, macOS, and Linux. -
3
Whisper-WebUI
A Web UI for easy subtitle using whisper model
...It supports multiple input sources including local files, YouTube content, and microphone input, making it versatile for different workflows. Whisper WebUI also includes advanced preprocessing and postprocessing features such as voice activity detection, background music separation, and speaker diarization, enabling more accurate and structured outputs. -
4
ESPnet
End-to-end speech processing toolkit
ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. This combination allows researchers to leverage modern neural architectures while still benefiting from the robust data preparation practices developed in the speech community. ... -
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5
pyVideoTrans
Translate the video from one language to another and embed dubbing
pyVideoTrans is an ambitious open-source multimedia processing project that assembles speech recognition, subtitle generation, AI translation, voice synthesis, and video assembly into a unified pipeline for converting videos from one language to another with embedded dubbing and captions. At its core it runs speech-to-text models to transcribe audio tracks, translates the resulting text into a target language using local or cloud-based translation engines, synthesizes new speech to match the... -
6
Scriberr
Self-hosted AI audio transcription
Scriberr is a self-hosted AI-powered transcription platform designed to convert audio and video into highly accurate text while prioritizing privacy and local processing. Unlike cloud-based transcription services, Scriberr runs entirely on the user’s machine, ensuring that sensitive recordings are never sent to third-party servers and remain fully under user control. It leverages modern speech recognition models such as Whisper and other advanced architectures to deliver precise transcripts... -
7
JSpeech
Java library designed to integrate Speech-to-Text
jSpeech is a Java library designed to integrate Speech-to-Text (STT) capabilities, command control, and diarization (speaker identification) into applications in a simple, modular, and decoupled way. -
8
SoniTranslate
Synchronized Translation for Videos
...It provides a web UI built with Gradio, allowing users to upload a video, choose source and target languages, and then run a pipeline that handles transcription, translation and re-synthesis of speech. Under the hood, it uses advanced speech and diarization models to separate speakers, align audio with timecodes and respect subtitle timing, which lets the generated dub track stay in sync with the original video structure. The project supports a wide range of languages for translation, spanning major world languages (English, Spanish, French, German, Chinese, Arabic, etc.) and many regional or less widely spoken languages, making it suitable for broad internationalization. ... -
9
Resemblyzer
A python package to analyze and compare voices with deep learning
...It works by turning speech audio into a compact voice embedding that represents the speaker’s vocal characteristics. These embeddings can then be used for speaker similarity, clustering, diarization experiments, voice comparison, and audio dataset exploration. The project is useful for researchers and developers who need a practical way to reason about speaker identity without building a voice encoder from scratch. It can help identify whether two recordings sound like the same speaker or visualize voice relationships across many samples. ... -
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