Generate text from audio input
Generate audio and SRT subtitles from text
Realtime implementation of Whisper large turbo
Generate speech from text with adjustable rate and pitch
Generate speech from text with adjustable speed
A demo of Indic Parler-TTS
High-fidelity Text-To-Speech
Turn text into speech with customizable voice, rate, and pitch
Convertir texto a audio
Text to Audio (Sound SFX) Generator
Spanish finetune for the original F5 model.
High-fidelity Text-To-Speech
Listen and respond to voice commands in Spanish
Nexa Omni Demo is a cutting-edge tool designed for Speech Synthesis, enabling users to generate high-quality text from audio input. It leverages advanced AI technology to deliver accurate and versatile transcription capabilities, making it ideal for a wide range of applications, including transcription services, voice assistants, and multilingual support.
• Multi-language Support: Transcribe audio in multiple languages with high accuracy.
• Real-time Transcription: Convert speech to text instantly, enabling live capturing of conversations or events.
• Speaker Identification: Distinguishes between multiple speakers in an audio file for clearer transcription.
• Noise Reduction: Minimizes background noise to improve transcription accuracy.
• Customizable Formats: Export transcriptions in various formats, including text, JSON, and more.
• Integration-ready: Easily integrate with other tools and platforms for seamless workflows.
What languages does Nexa Omni Demo support?
Nexa Omni Demo supports a wide range of languages, including English, Spanish, French, Mandarin, and many others. For a full list, refer to the official documentation.
How accurate is the transcription?
The accuracy depends on the quality of the audio input. With clear audio, Nexa Omni Demo achieves high accuracy, typically above 90%. Background noise or poor audio quality may reduce accuracy.
Can I customize the transcription output?
Yes, you can customize the output by selecting different formats (e.g., text, JSON) and adjusting settings such as speaker identification and timestamp inclusion.