Results for “audio-translation”

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

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.

Transcribe audio files to text with optional speaker diarization and known-speaker hints using OpenAI models.

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.

Transform the voice in an audio recording into a different target voice while preserving emotion, timing, and delivery using the ElevenLabs Voice Changer API.

Transcribe audio files to text using local speech recognition. Triggers on: "转录", "transcribe", "语音转文字", "ASR", "识别音频", "把这段音频转成文字".

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.

Transcribe audio via OpenAI Audio Transcriptions API (Whisper).

Translate text faithfully into a target language while preserving meaning, register, and intent.

Translate text between languages with cultural adaptation, terminology consistency, and support for multiple document types including technical docs, marketing copy, and UI strings. Use when the user requests translation or provides relevant inputs for this workflow.

OpenAI Audio Transcriptions API via curl; gpt-4o-transcribe, mini, diarize, or whisper-1.

Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.

Transcrever arquivos de áudio para texto com diarização opcional e dicas de falantes conhecidos. Use quando um usuário pedir para transcrever fala de áudio/vídeo, extrair texto de gravações ou identificar falantes em entrevistas ou reuniões.

Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.

Transcribe meeting audio with speaker diarization, generate structured summaries with action items, decisions, and follow-ups, and support multiple audio formats and languages. Use when the user requests meeting transcription or provides relevant inputs for this workflow.

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

Transcribe audio files using Qwen ASR. Use when the user sends voice messages and wants them converted to text.

Transcribe WhatsApp voice messages using local Whisper CLI. Use when: owner or contact sends an audio/ogg voice message. Combines Whisper transcription + CRM update + task creation. Works offline for short clips, uses OpenAI API for long clips. Hebrew and English supported.

Text-to-speech and speech-to-text using fal.ai audio models

Convert text to speech and speech to text using fal.ai audio models.

用自然语言描述生成目标音频。把一段场景描述（人声对话、环境声、音效、背景音乐等复合音频）一次性生成成音频。当用户描述一个声音场景、要求生成/合成/制作一段音频或声音、给出形如"角色：台词"的对话脚本要转成音频、或要按参考音频的音色说话时使用。支持两种模式：纯文本描述生成（T2A）和带参考音频生成（A2A，在描述中引用参考音频指定角色音色）

Transforms video or audio transcripts into structured markdown documentation, organizing content by topic with configurable styles and source attribution.

Translates text between languages with three modes: quick, normal, and refined. Supports custom glossaries, audience targeting, and style presets.

Text-to-speech and speech-to-text using fal.ai audio models

Text-to-speech and speech-to-text using fal.ai audio models

See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

Converts text to speech and generates MP3 audio files using Hume AI or OpenAI APIs, printing the file path for delivery.