

Streamspeech
Overview :
StreamSpeech is a real-time speech-to-speech translation model based on multi-task learning. By learning translation and synchronization strategies in a unified framework, it effectively identifies the translation timing within streaming voice input, achieving a high-quality real-time communication experience. The model has demonstrated leading performance on the CVSS benchmark and can provide low-latency intermediate results, such as ASR or translation.
Target Users :
StreamSpeech is designed for professionals who require real-time cross-language communication, such as simultaneous interpreters at international conferences, multilingual business communicators, and language learners. By minimizing translation delays and enhancing communication efficiency, StreamSpeech enables seamless real-time conversations between individuals from diverse linguistic backgrounds.
Use Cases
Simultaneous interpretation at international conferences using StreamSpeech.
Cross-national companies use StreamSpeech for remote meetings, enabling real-time multilingual communication.
Language learners use StreamSpeech to practice listening and speaking skills in different languages.
Features
Supports streaming speech recognition (ASR)
Supports non-autoregressive speech-to-text translation (NAR-S2TT)
Supports speech-to-unit translation (S2UT)
Can generate target speech in real-time
Provides high-quality intermediate results during translation
Supports translation between multiple languages, such as French-English, Spanish-English, and German-English
How to Use
1. Visit the StreamSpeech website and familiarize yourself with the product information.
2. Select the source and target languages and make any necessary settings.
3. Upload or input real-time source language voice data.
4. The system will automatically recognize the speech and translate it.
5. The translated speech will be output in the target language.
6. During translation, you can view the intermediate ASR or translation results in real-time.
7. Adjust the translation parameters based on feedback to optimize translation quality.
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