Model overview
Open Whisper-style Speech Model (OWSM) is the first **fully open** Whisper-style speech foundation model. It reproduces and advances OpenAI's Whisper-style training using publicly available data and open-source toolkits. The code, pre-trained model weights, and training logs are publicly released to promote open science in speech foundation models. OWSM-CTC (Peng et al., ACL 2024) is a novel encoder-only speech foundation model based on hierarchical multi-task self-conditioned CTC. It supports multilingual speech recognition, speech translation, and language identification within a single non-autoregressive model. OWSM-CTC v4 is trained for three epochs on 320k hours of public audio data covering multilingual speech recognition, any-to-any speech translation, and language identification. The newly curated data are publicly released: https://huggingface.co/datasets/espnet/yodas_owsmv4
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
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
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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：cc-by-4.0。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。