stt

A new speech-to-text tool claims to rival Dragon Professional on Windows, offering a competitive alternative for voice recognition.

Describes a medical speech-to-text system that runs locally on a MacBook, enabling streaming transcription without cloud dependency.

The author argues that for live voice agents, STT latency and real-time behavior are more critical than raw transcription accuracy, and proposes a different evaluation scorecard.

A developer debunks the common belief that LLM latency is the primary cause of slow voice agents, explaining that delays often stem from earlier stages like audio capture, VAD, and STT. They recommend logging specific latency metrics and testing various STT/TTS providers and orchestration frameworks to diagnose issues.

A curated, open-source learning path for building voice agents, covering from STT to production, with 190+ resources and a 5-week plan.

pibot is now fully local, using Parakeet for STT, Qwen3-tts for TTS, and Qwen 3.6 as the local multimodal LLM via llama.cpp, with Rust/mlx-c based inference engines, achieving zero Python dependencies.

Interfaze introduces a new hybrid AI model architecture that combines DNN/CNN encoders with transformers to achieve superior accuracy and cost-efficiency for deterministic tasks such as OCR, vision, and STT, compared to generalist models.

A new AI model from interfaze_ai claims to outperform leading models (sonnet 4.6, gemini 3 flash, gpt 5.4 mini) on OCR, vision, and speech-to-text tasks.