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Model
Riva TTS A²-Flow model for the NVIDIA In-Game Inferencing (NVIGI) SDK.
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| Field | Response |
|---|---|
| Intended Application & Domain: | Speech Synthesis |
| Model Task | Speech Synthesis and Voice Characterization |
| Intended Users | This model is intended for developers building interactive call centers, virtual assistants, and language learning assistants to improve pronunciation, automatically generate voice-overs, narrate or comment on videos, and provide audio alternatives for visually impaired users or people with light sensitivity. |
| Model Output | Audio of shape (batch x time) in wav format |
| Describe how the model works | Model takes input text and outputs an audio representation of the text. It can be used as a zero-shot voice characterization model. When given a reference audio sample to replicate along with an input text, the produced synthetic audio will be similar to this reference. |
| Name the adversely impacted groups this has been tested to deliver comparable outcomes regardless of | Gender, Age (including people in older age brackets) |
| Technical Limitations | Model only has the capacity to produce a voice in the languages, dialects and gender(s) in which it is trained. This model makes no effort to moderate or modify input text. Languages that are underrepresented may not sound as natural. |
| Verified to have met prescribed NVIDIA quality standards | Yes |
| Performance Metrics | % preference when compared with available alternatives word error rate (wer) character error rate (cer) mean opinion score (MOS) |
| Potential Known Risks | This model has the ability to replicate the characteristics of an individual's voice but may unnaturally synthesize vocabulary not included in the pronunciation dictionary or omit phonetic symbols not used in training. |
| Licensing: | https://docs.nvidia.com/ai-foundation-models-community-license.pdf |