Results for “speech-cloning”

Generate natural AI voices, text-to-speech, and voice synthesis using the inference.sh CLI with models like Inworld TTS, ElevenLabs, and Kokoro TTS for voiceovers, audiobooks, podcasts, and more.

Generates speech, transcribes audio, clones voices, and builds real-time voice agents using ElevenLabs, OpenAI TTS, Whisper, and Vapi.

Generate spoken audio for narration, voiceovers, IVR prompts, and accessibility reads using the OpenAI Audio API with bundled CLI and built-in voices.

Generates spoken audio clips from text for narration, voiceovers, IVR prompts, and accessibility reads, with support for single clips and batch processing.

Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features and classifying samples with machine learning models.

Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.

Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.

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

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

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

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

Use this skill whenever the user wants to convert text into speech, generate audio from text, or produce voiceovers. Triggers include: any mention of 'TTS', 'text to speech', 'speak', 'say', 'voice', 'read aloud', 'audio narration', 'voiceover', 'dubbing', or requests to turn written content into spoken audio. Also use when converting EPUB/PDF/SRT/articles to audio, cloning voices from reference audio, controlling emotion or speed in speech, aligning speech to subtitle timelines, or producing per-segment voice-mapped audio.

Use quando o usuário solicita narração em texto-para-fala, voiceovers de acessibilidade, prompts de áudio ou geração em lote via OpenAI Audio API; execute a CLI incluída (`scripts/text_to_speech.py`) com vozes integradas e requer `OPENAI_API_KEY` para chamadas diretas. Criação de vozes customizadas está fora do escopo.

Local speech-to-text with the Whisper CLI (no API key).

Use when the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.

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

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

Local speech-to-text with the Whisper CLI (no API key).

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

Generate natural speech from text using ElevenLabs voice AI, supporting 70+ languages, multiple models, and various output formats.

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 with optional speaker diarization and known-speaker hints using OpenAI models.

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

Transcribe audio to text using ElevenLabs Scribe and Whisper models via the inference.sh CLI, supporting timestamps, speaker diarization, translation, and multi-language transcription.

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

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.

Lip-sync a face to a specific audio track on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar from a portrait + audio), Sync Labs sync v2 / Pro (state-of-the-art mouth sync onto a video), Kling lipsync (audio-to- video and text-to-video with synced speech), and Creatify lipsync. The skill picks the right endpoint for the user's actual intent — portrait still + audio (avatar-style), source video + audio (mouth- swap on existing footage), or generate-and-sync from a script. Triggers on "lip sync", "lipsync", "make this video speak", "match audio to mouth", "dub video", "sync lips to voice", "Sync Labs", "voiceover sync", or any explicit ask to drive a face's mouth from an audio track.

Fast, accurate, and incredibly inexpensive automatic speech-to-text transcription service.

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

Generate spoken audio from text using OpenAI's API with built-in voices for narrated explainers, lecture audio, and quick voiceover tracks.

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.