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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.00965 |
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| _version_ | 1866917775471017984 |
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| author | Wilmet, Vincent Du, Johnson |
| author_facet | Wilmet, Vincent Du, Johnson |
| contents | This paper presents an in-depth analysis of the latency characteristics observed in simultaneous speech-to-speech model's performance, particularly focusing on hallucination-induced latency spikes. By systematically experimenting with various input parameters and conditions, we propose methods to minimize latency spikes and improve overall performance. The findings suggest that a combination of careful input management and strategic parameter adjustments can significantly enhance speech-to-speech model's latency behavior. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_00965 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | What does it take to get state of the art in simultaneous speech-to-speech translation? Wilmet, Vincent Du, Johnson Computation and Language This paper presents an in-depth analysis of the latency characteristics observed in simultaneous speech-to-speech model's performance, particularly focusing on hallucination-induced latency spikes. By systematically experimenting with various input parameters and conditions, we propose methods to minimize latency spikes and improve overall performance. The findings suggest that a combination of careful input management and strategic parameter adjustments can significantly enhance speech-to-speech model's latency behavior. |
| title | What does it take to get state of the art in simultaneous speech-to-speech translation? |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2409.00965 |