Speech Recognition
anomalyco/hex๐ฅ active
โฒ +1.2K โ this week
Local voice dictation for mac, windows and linux
RustMITupdated Nov 12, 2026
๐ฅ Trending this week in Speech Recognition
Speech Recognition
wquguru/cicada๐ฅ active
โฒ +756 โ this week
็ฅไบ Cicada ยท ไปปไฝไผ่ฎฎๅ็ดๆญ็ๅฎๆถๅญๅนใๅๅฃฐไผ ่ฏใAI ไผ่ฎฎ็บช่ฆ๏ผMacใWindowsใLinuxใAndroid ๅ ่ดนๅผๆบใLive subtitles, interpreting and meeting notes for any call or stream, on Mac, Windows, Linux and Android.
SwiftApache-2.0updated Nov 12, 2026
Speech Recognition
huggingface/transformers๐ฅ active
โฒ +336 โ this week
๐ค Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
๐ง Natural Language Processing
PythonApache-2.0updated Nov 12, 2026
Speech Recognition
SYSTRAN/faster-whisper๐ฅ active
โฒ +190 โ this week
Faster Whisper transcription with CTranslate2
PythonMITupdated Nov 12, 2026
Speech Recognition
ggml-org/whisper.cpp๐ฅ active
โฒ +185 โ this week
Port of OpenAI's Whisper model in C/C++
C++MITupdated Nov 10, 2026
Speech Recognition
m-bain/whisperX
โฒ +136 โ this week
WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
PythonBSD-2-Clauseupdated Oct 22, 2026
Top 30 speech-to-text tools by stars
Speech Recognition๐ฅ#1
huggingface/transformers๐ฅ active
โฒ +336 โ this week
๐ค Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
๐ง Natural Language Processing
PythonApache-2.0updated Nov 12, 2026
Speech Recognition๐ฅ#2
debpalash/VoiceStudio๐ฅ active
VoiceStudio is the open-source, fully-local ElevenLabs alternative โ voice cloning, voice design, video dubbing, dictation, transcription & audiobook creation in 646 languages.
PythonAGPL-3.0updated Nov 12, 2026
Speech Recognition๐ฅ#3
ggml-org/whisper.cpp๐ฅ active
โฒ +185 โ this week
Port of OpenAI's Whisper model in C/C++
C++MITupdated Nov 10, 2026
Speech Recognition#4
cjpais/Handy๐ฅ active
A free, open source, and extensible speech-to-text application that works completely offline.
RustMITupdated Nov 12, 2026
Speech Recognition#5
Zackriya-Solutions/meetily๐ฅ active
Privacy-first AI meeting note taker for Windows and macOS. Free, open source (MIT). On-device Whisper/Parakeet transcription and speaker diarization, no meeting bot. Open-source alternative to Granola, Otter and Fireflies. https://meetily.ai
RustMITupdated Nov 12, 2026
Speech Recognition#6
SYSTRAN/faster-whisper๐ฅ active
โฒ +190 โ this week
Faster Whisper transcription with CTranslate2
PythonMITupdated Nov 12, 2026
Speech Recognition#7
mozilla-ai/llamafile๐ฅ active
Distribute and run LLMs with a single file.
C++Otherupdated Nov 9, 2026
Speech Recognition#8
m-bain/whisperX
โฒ +136 โ this week
WhisperX: Automatic Speech Recognition with Word-level Timestamps (& Diarization)
PythonBSD-2-Clauseupdated Oct 22, 2026
Speech Recognition#9
screenpipe/screenpipe๐ฅ active
YC (S26) | Open Computer History | Continuously record your company computer work, map your workflows, help you find work worth automating, and power your agents' context
RustOtherupdated Nov 12, 2026
Speech Recognition#10
Evil0ctal/Douyin_TikTok_Download_API๐ฅ active
๐ ่ชๆ็ฎก็ๆ้ณใTikTokใB ็ซๆฐๆฎ้้ไธๆ ๆฐดๅฐ่ง้ขไธ่ฝฝ API๏ผๆฏๆ AI agent ้่ฟ MCP ่ฐ็จไธ็ฆป็บฟ่ฏญ้ณ่ฝฌๆๅญ๏ผDocker ไธ้ฎ้จ็ฝฒใ| Self-hosted TikTok, Douyin & Bilibili scraper and no-watermark video downloader โ async REST API, MCP server for AI agents, CLI and web console, plus offline speech-to-text for downloaded videos. Self-healing identity pool, PostgreSQL archive, one docker compose up.
PythonApache-2.0updated Nov 9, 2026
Speech Recognition#11
modelscope/FunASR๐ฅ active
โฒ +59 โ this week
Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.
PythonMITupdated Nov 11, 2026
Speech Recognition#12
jianchang512/pyvideotrans๐ฅ active
Translate the video from one language to another and embed dubbing & subtitles.
PythonGPL-3.0updated Nov 12, 2026
Speech Recognition#13
NVIDIA-NeMo/Speech๐ฅ active
โฒ +40 โ this week
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
๐ Machine Translation
PythonApache-2.0updated Nov 12, 2026
Speech Recognition#14
leon-ai/leon๐ฅ active
โฒ +24 โ this week
๐ง Leon is your open-source personal assistant.
TypeScriptMITupdated Nov 12, 2026
Speech Recognition#15
k2-fsa/sherpa-onnx๐ฅ active
Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages
C++Apache-2.0updated Nov 12, 2026
Speech Recognition#16
kaldi-asr/kaldi
โฒ +7 โ this week
kaldi-asr/kaldi is the official location of the Kaldi project.
ShellOtherupdated Sep 22, 2025
Speech Recognition#17
alphacep/vosk-api
โฒ +22 โ this week
Offline speech recognition API for Android, iOS, Raspberry Pi and servers with Python, Java, C# and Node
Jupyter NotebookApache-2.0updated Oct 15, 2026
Speech Recognition#18
NVIDIA/DeepLearningExamples
โฒ +4 โ this week
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
๐ค Language Models๐ง Natural Language Processing
Jupyter Notebookno licenseupdated Aug 12, 2024
Speech Recognition#19
huggingface/speech-to-speech๐ฅ active
โฒ +42 โ this week
Build voice agents with open-source models
๐ค Language Models
PythonApache-2.0updated Nov 12, 2026
Speech Recognition#20
abus-aikorea/voice-pro
โฒ +19 โ this week
Gradio WebUI for creators and developers, featuring key TTS (Edge-TTS, kokoro) and zero-shot Voice Cloning (E2 & F5-TTS, CosyVoice), with Whisper audio processing, YouTube download, Demucs vocal isolation, and multilingual translation.
PythonGPL-3.0updated Jul 13, 2026
Speech Recognition#21
kmario23/deep-learning-drizzle
โฒ +8 โ this week
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
๐ง Natural Language Processing
HTMLno licenseupdated Aug 22, 2026
Speech Recognition#22
PaddlePaddle/PaddleSpeech
โฒ +2 โ this week
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
PythonApache-2.0updated Aug 12, 2026
Speech Recognition#23
speechbrain/speechbrain
โฒ +12 โ this week
A PyTorch-based Speech Toolkit
๐ค Language Models
PythonApache-2.0updated Oct 14, 2026
Speech Recognition#24
OpenWhispr/openwhispr๐ฅ active
Voice-to-text dictation app with local (Nvidia Parakeet/Whisper) and cloud models (BYOK). Privacy-first and available cross-platform.
JavaScriptMITupdated Nov 12, 2026
Speech Recognition#25
QuentinFuxa/WhisperLiveKit๐ฅ active
โฒ +22 โ this week
Real-time, local speech-to-text with streaming ASR, speaker diarization, translation, and OpenAI/Deepgram-compatible APIs.
PythonApache-2.0updated Nov 8, 2026
Speech Recognition#26
openvinotoolkit/openvino๐ฅ active
โฒ +35 โ this week
OpenVINOโข is an open source toolkit for optimizing and deploying AI inference
๐ง Natural Language Processing
C++Apache-2.0updated Nov 12, 2026
Speech Recognition#27
nexmoe/VidBee๐ฅ active
Download video and audio from 1000+ sites, transcribe locally with speaker labels, and summarize, translate, or chat with your media using your preferred AI provider.
TypeScriptMITupdated Nov 8, 2026
Speech Recognition#28
KoljaB/RealtimeSTT๐ฅ active
A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.
PythonApache-2.0updated Nov 11, 2026
Speech Recognition#29
espnet/espnet๐ฅ active
โฒ +10 โ this week
End-to-End Speech Processing Toolkit
๐ Machine Translation
PythonApache-2.0updated Nov 11, 2026
Speech Recognition#30
QwenAudio/SenseVoice
โฒ +48 โ this week
Open-source SenseVoiceSmall model for Mandarin, Cantonese, English, Japanese, and Korean ASR, language ID, emotion recognition, and audio event detection.
๐ Sentiment Analysis
CMITupdated Sep 30, 2026
๐ New research on Speech Recognition
๐ arXiv:2611.14421 ยท cs.SD46h ago
Earlybird: Predictive Streaming Speech Recognition in 29M Parameters
Sahil Mahendrakar
๐ฌ 9 pages, 3 figures, 6 tables. Model: https://huggingface.co/sahilmahendrakar/Earlybird-29M
Streaming speech recognizers output a word only after the speaker has finished it, typically 90-400 ms later. For a voice agent every millisecond counts: the sooner the words are outputted, the sooner the agent can start a search or plan its reply. We present Earlybird, a 29M-parameter streaming recognizer (16.8 MB at 4 bits). Earlybird learns from audio cut off at random points, including partway through a word, and is asked to predict every word that is due by then in full, plus a guess of the next two words. Its raw token probabilities give a confidence for every word including the one still being spoken. On clean audiobook speech (LibriSpeech test-clean), the median word is predicted correctly 90 ms before the speaker finishes it, while released streaming models get it 90 to 400 ms after it ends. Earlybird is the earliest on all six test sets we time, covering audiobooks, TED talks, public speech, earnings calls, and synthetic speech. On the same audiobooks, 69% of words are predicted correctly before they end, against 3-25% for the other models. For words still being spoken, confidence is calibrated, with an expected calibration error (ECE) of 3.7 to 5.5. On the eight English Open ASR Leaderboard sets, it is more accurate than Moonshine Tiny on every set and roughly ties Whistle, a model of the same size.โผ more
๐๏ธ Speech Recognition
๐ arXiv:2611.14241 ยท cs.CL2d ago
Dyship: Leveraging Acoustic Features For Speaker Relationship Classification From Dyadic Conversations
Kieran Sturges, Thomas Thebaud, Yaohan Guan +1
๐ฌ 5 pages, under review
We introduce DyShip, a framework for classifying speaker familiarity and kinship from dyadic conversations in the Seamless Interaction corpus. We compare five speech representations: spectrograms, MFCCs, self-supervised WavLM representations, x-vectors, and estimated articulatory movements. Spectral features perform best for familiarity classification, reaching an accuracy of 87.81%, while WavLM achieves the highest kinship accuracy of 85.17%. X-vectors and articulatory features yield weaker results on familiarity classifiaction, but shine for kinship classification, with an AUC of 0.909 for x-vectors. Most classifiers exceed previously reported human and audio language model scores on the same dataset. These findings highlight the potential of conventional acoustic features for relationship inference and motivate further investigation of the conversational cues captured by different representations.โผ more
๐๏ธ Speech Recognition๐ค Language Models
๐ arXiv:2611.14036 ยท cs.CL2d ago
MISO-BR: An Open Corpus for Misogyny Detection in Brazilian Portuguese
Fรกbio A. S. Passos, Pรฉricles B. C. Miranda, Ana Paula Cavalcanti
Misogyny is among the most prevalent forms of online hate speech directed at Brazilian users, yet open and auditable resources dedicated to it in Brazilian Portuguese remain scarce. We introduce MISO-BR, an open, documented and versioned corpus of 896 balanced social media texts annotated for binary misogyny, released with its construction protocol and reproducible baselines. The corpus combines lexicon- and target-guided scraping from X with items imported from OLID-BR, a large language model triage stage whose prompt and decoding parameters are released, and manual annotation by three annotators following a written guide. Inter-annotator reliability reaches a Fleiss' kappa of 0.788 over 816 items. Under a single fixed protocol we compare four classical classifiers (Multinomial and Bernoulli Naive Bayes, a linear SVM and a random forest) with fine-tuned BERTimbau Base and Large. The classical models cluster between 0.651 and 0.676 macro-F1 and are precision-oriented but recall-poor. The transformers reach 0.833 macro-F1 and accuracy (Wilson 95% CI for accuracy [0.77, 0.88]), a gap of roughly 16 points, while Base and Large are indistinguishable on the test set despite a 2.6x difference in training cost. We argue that the value of the resource lies less in its headline scores than in the auditability of its pipeline, and we state three limits that users must reckon with: the artificial class balance, whose effect on precision under realistic prevalence we quantify; the association between provenance and label, which the released source field makes measurable; and the selection bias induced by lexicon-guided sampling and automatic triage. The corpus, annotation guide, models and experimental scripts are publicly available.โผ more
๐๏ธ Text Classification๐๏ธ Speech Recognition๐ค Language Models
๐ arXiv:2611.13990 ยท cs.CL2d ago
On the information rate of phones, syllables and words
Herman Kamper
๐ฌ 5 pages, 1 table, 2 figures
Which linguistic units minimise the bitrate required to encode speech content: phones, syllables, words, maybe larger units, or something in between? This question has implications for the development of speech and language systems and theories of human language processing. Using a transcribed corpus of 960 hours of English audiobooks, I compare the information rates of phones, syllables, words, multi-word combinations and intermediate tokenisations. While all units are equivalent under a perfect language model, it makes sense to compare these under limited modelling budgets; I use $n$-gram and transformer language models. The lowest bitrates are achieved using words, with slightly longer units sometimes performing best. The results show that, when modelling capacity is limited, units larger than syllables but smaller than long multi-word phrases provide the most efficient representation in terms of information rate.โผ more
โ๏ธ Tokenization & Preprocessing๐๏ธ Speech Recognition๐ค Language Models