Model overview
Fine-tuned facebook/wav2vec2-base-fr-voxpopuli-v2 for **French speech-to-phoneme** (without language model) using the train and validation splits of Common Voice v13. As this model is specifically trained for a speech-to-phoneme task, the output is sequence of IPA-encoded words, without punctuation. If you don't read the phonetic alphabet fluently, you can use this excellent IPA reader website to convert the transcript back to audio synthetic speech in order to check the quality of the phonetic transcription. The model has been finetuned on Commonvoice-v13 (FR) for 14 epochs on a 4x2080 Ti GPUs at Cnam/LMSSC using a ddp strategy and gradient-accumulation procedure (256 audios per update, corresponding roughly to 25 minutes of speech per update -> 2k updates per epoch)
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
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| Source / channel | Input | Output | Billing unit | Collected at |
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Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
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Sources & traceability
许可证：mit。模型介绍与第三方评测均以原来源的具体版本和方法为准。