Results for “audio-transcription”

Transcribe audio files to text using the z-ai-web-dev-sdk, with CLI and SDK examples for single files, batches, and directories.

Extract semantic content from documents, images, audio, and video using Azure AI Content Understanding SDK for Python.

Transcribe audio to text using ElevenLabs Scribe v2, supporting 90+ languages, speaker diarization, and word-level timestamps.

Transcribe audio with high accuracy using ElevenLabs Scribe models, supporting speaker diarization, audio event tagging, forced alignment, and subtitle generation via the inference.sh CLI.

Transcribes audio from URLs or local files into text with speaker diarization, word timestamps, and multiple output formats via a command-line tool.

Transcribe and translate audio across 99 languages using OpenAI's Whisper model, with options for model size, language detection, timestamps, and batch processing.

Transcribes audio from URLs or local files to text using the Speech is Cheap API, with options for speaker diarization, timestamps, and multiple output formats.

Ingest, index, search, and edit video and audio from files, URLs, live streams, or desktop sessions with timestamps, subtitles, overlays, and real-time alerts.

Transcribe and translate speech across 99 languages using OpenAI's Whisper model, with support for multiple model sizes, batch processing, and subtitle generation.

Generates spectrograms and multi-panel audio feature visualizations (mel, chroma, MFCC) from audio files via a Go CLI.

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

Transcribes audio from URLs or local files into text using a low-cost speech-to-text API, with options for speaker diarization, word timestamps, and multiple output formats.

Audio spectrograms/features (mel, chroma, MFCC) via CLI.

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

Benchmarks automatic speech translation and recognition on English-French and English-Romanian datasets, reporting BLEU and WER on tokenized outputs.

OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

Generates spectrograms and multi-panel audio feature visualizations from audio files via a command-line tool.

Transcribe short audio files (up to 60 seconds) using Azure Speech-to-Text REST API with Python, without requiring the Speech SDK.

Generates and burns subtitles into videos: extracts audio, transcribes via Volcano Engine, corrects errors, reviews, and burns subtitles with ffmpeg.

Ingest, index, search, edit, and generate video and audio content from files, URLs, live streams, or desktop capture.