AI Briefing#asr
The latest AI and developer news about #asr, with the original source and a short summary.
The latest AI and developer news about #asr, with the original source and a short summary.
For Somali TTS, XTTS V4 works best so far, but the LLM and Whisper layers remain bottlenecks.
Scribe v2 Realtime delivers STT for real-time agents with ultra-low latency of 30-80ms.
ElevenLabs has unveiled Scribe, an STT model supporting 99 languages with industry-leading accuracy.
To reduce the latency that determines the immersiveness of conversational AI, the latency of each stage—ASR, TTI, LLM, and more—must be managed holistically.
Cohere has released Transcribe, an open-source ASR model supporting 14 languages.
Google has launched 'Google AI Edge Eloquent,' an offline-first AI dictation app based on the Gemma model, on iOS.
Qwen3-ASR and ForcedAligner have been open-sourced, strengthening multilingual and streaming speech recognition.
HuggingFace announced an update to the Open ASR Leaderboard that adds multilingual and long-form tracks, along with the latest trends in speech recognition.
Hugging Face has launched an Inference Endpoints option that boosts Whisper transcription performance by up to 8x using vLLM.
It introduces how to implement a custom handler that combines Whisper and Pyannote in Hugging Face Inference Endpoints to support speaker diarization and speculative decoding.
This covers how to use Meta's Wav2Vec2-BERT to improve automatic speech recognition (ASR) performance for languages with limited data.
This introduces a method for efficiently boosting ASR performance for low-resource languages by fine-tuning Meta's MMS model using an adapter approach.
This guide explains how to fine-tune the Whisper model on multilingual automatic speech recognition (ASR) datasets using Hugging Face Transformers.
This explains how to leverage the characteristics of the CTC architecture to perform high-quality speech recognition on long audio files without memory issues.
This explains a fine-tuning method that uses Hugging Face's XLS-R model to improve speech recognition (ASR) performance for low-resource languages.