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  # Step-Audio-TTS-3B
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- Step-Audio-TTS-3B 是业界首个基于大规模合成数据和LLM-Chat范式训练的TTS模型，在SEED TTS Eval上取得SOTA的CER结果，支持多种语言，多种情感，多种语音风格控制，也是业界首个支持RAP和哼唱的TTS模型。
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- Step-Audio-TTS-3B represents the industry's first Text-to-Speech (TTS) model trained on a large-scale synthetic dataset utilizing the LLM-Chat paradigm. It has achieved SOTA Character Error Rate (CER) results on the SEED TTS Eval benchmark. The model supports multiple languages, a variety of emotional expressions, and diverse voice style controls. Notably, Step-Audio-TTS-3B is also the first TTS model in the industry capable of generating RAP and Humming, marking a significant advancement in the field of speech synthesis.
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- 本仓库提供采用dual-codebook训练的StepAudio-TTS-3B LLM 模型权重，基于dual-codebook训练的vocoder，以及为哼唱专门训练的vocoder。
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- This repository provides the model weights for StepAudio-TTS-3B, which is a dual-codebook trained LLM (Large Language Model) for text-to-speech synthesis. Additionally, it includes a vocoder trained using the dual-codebook approach, as well as a specialized vocoder specifically optimized for humming generation. These resources collectively enable high-quality speech synthesis and humming capabilities, leveraging the advanced dual-codebook training methodology.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- 更多信息请参考我们的仓库： [Step-Audio](https://github.com/stepfun-ai/Step-Audio).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  For more information, please refer to our repository: [Step-Audio](https://github.com/stepfun-ai/Step-Audio).
 
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  # Step-Audio-TTS-3B
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+ Step-Audio-TTS-3B represents the industry's first Text-to-Speech (TTS) model trained on a large-scale synthetic dataset utilizing the LLM-Chat paradigm. It has achieved SOTA Character Error Rate (CER) results on the SEED TTS Eval benchmark. The model supports multiple languages, a variety of emotional expressions, and diverse voice style controls. Notably, Step-Audio-TTS-3B is also the first TTS model in the industry capable of generating RAP and Humming, marking a significant advancement in the field of speech synthesis.
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+ This repository provides the model weights for StepAudio-TTS-3B, which is a dual-codebook trained LLM (Large Language Model) for text-to-speech synthesis. Additionally, it includes a vocoder trained using the dual-codebook approach, as well as a specialized vocoder specifically optimized for humming generation. These resources collectively enable high-quality speech synthesis and humming capabilities, leveraging the advanced dual-codebook training methodology.
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+ ## Performance comparison of content consistency (CER/WER) between GLM-4-Voice and MinMo.
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+ <table>
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+ <thead>
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+ <tr>
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+ <th rowspan="2">Model</th>
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+ <th style="text-align:center" colspan="1">test-zh</th>
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+ <th style="text-align:center" colspan="1">test-en</th>
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+ </tr>
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+ <tr>
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+ <th style="text-align:center">CER (%) &darr;</th>
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+ <th style="text-align:center">WER (%) &darr;</th>
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+ </tr>
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+ </thead>
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+ <tbody>
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+ <tr>
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+ <td>GLM-4-Voice</td>
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+ <td style="text-align:center">2.19</td>
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+ <td style="text-align:center">2.91</td>
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+ </tr>
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+ <tr>
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+ <td>MinMo</td>
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+ <td style="text-align:center">2.48</td>
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+ <td style="text-align:center">2.90</td>
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+ </tr>
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+ <tr>
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+ <td><strong>Step-Audio</strong></td>
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+ <td style="text-align:center"><strong>1.53</strong></td>
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+ <td style="text-align:center"><strong>2.71</strong></td>
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+ </tr>
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+ </tbody>
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+ </table>
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+ ## Results of TTS Models on SEED Test Sets.
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+ * StepAudio-TTS-3B-Single denotes dual-codebook backbone with single-codebook vocoder*
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+
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+ <table>
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+ <thead>
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+ <tr>
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+ <th rowspan="2">Model</th>
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+ <th style="text-align:center" colspan="2">test-zh</th>
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+ <th style="text-align:center" colspan="2">test-en</th>
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+ </tr>
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+ <tr>
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+ <th style="text-align:center">CER (%) &darr;</th>
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+ <th style="text-align:center">SS &uarr;</th>
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+ <th style="text-align:center">WER (%) &darr;</th>
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+ <th style="text-align:center">SS &uarr;</th>
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+ </tr>
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+ </thead>
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+ <tbody>
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+ <tr>
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+ <td>FireRedTTS</td>
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+ <td style="text-align:center">1.51</td>
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+ <td style="text-align:center">0.630</td>
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+ <td style="text-align:center">3.82</td>
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+ <td style="text-align:center">0.460</td>
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+ </tr>
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+ <tr>
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+ <td>MaskGCT</td>
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+ <td style="text-align:center">2.27</td>
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+ <td style="text-align:center">0.774</td>
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+ <td style="text-align:center">2.62</td>
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+ <td style="text-align:center">0.774</td>
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+ </tr>
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+ <tr>
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+ <td>CosyVoice</td>
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+ <td style="text-align:center">3.63</td>
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+ <td style="text-align:center">0.775</td>
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+ <td style="text-align:center">4.29</td>
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+ <td style="text-align:center">0.699</td>
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+ </tr>
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+ <tr>
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+ <td>CosyVoice 2</td>
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+ <td style="text-align:center">1.45</td>
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+ <td style="text-align:center">0.806</td>
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+ <td style="text-align:center">2.57</td>
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+ <td style="text-align:center">0.736</td>
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+ </tr>
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+ <tr>
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+ <td>CosyVoice 2-S</td>
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+ <td style="text-align:center">1.45</td>
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+ <td style="text-align:center">0.812</td>
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+ <td style="text-align:center">2.38</td>
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+ <td style="text-align:center">0.743</td>
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+ </tr>
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+ <tr>
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+ <td><strong>Step-Audio-TTS-3B-Single</strong></td>
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+ <td style="text-align:center">1.37</td>
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+ <td style="text-align:center">0.802</td>
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+ <td style="text-align:center">2.52</td>
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+ <td style="text-align:center">0.704</td>
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+ </tr>
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+ <tr>
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+ <td><strong>Step-Audio-TTS-3B</strong></td>
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+ <td style="text-align:center"><strong>1.31</strong></td>
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+ <td style="text-align:center">0.733</td>
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+ <td style="text-align:center"><strong>2.31</strong></td>
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+ <td style="text-align:center">0.660</td>
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+ </tr>
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+ <tr>
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+ <td><strong>Step-Audio-TTS</strong></td>
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+ <td style="text-align:center"><strong>1.17</strong></td>
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+ <td style="text-align:center">0.73</td>
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+ <td style="text-align:center"><strong>2.0</strong></td>
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+ <td style="text-align:center">0.660</td>
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+ </tr>
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+ </tbody>
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+ </table>
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+
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+ ## Performance comparison of Dual-codebook Resynthesis with Cosyvoice.
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+ <table>
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+ <thead>
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+ <tr>
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+ <th style="text-align:center" rowspan="2">Token</th>
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+ <th style="text-align:center" colspan="2">test-zh</th>
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+ <th style="text-align:center" colspan="2">test-en</th>
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+ </tr>
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+ <tr>
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+ <th style="text-align:center">CER (%) &darr;</th>
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+ <th style="text-align:center">SS &uarr;</th>
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+ <th style="text-align:center">WER (%) &darr;</th>
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+ <th style="text-align:center">SS &uarr;</th>
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+ </tr>
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+ </thead>
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+ <tbody>
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+ <tr>
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+ <td style="text-align:center">Groundtruth</td>
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+ <td style="text-align:center">0.972</td>
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+ <td style="text-align:center">-</td>
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+ <td style="text-align:center">2.156</td>
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+ <td style="text-align:center">-</td>
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+ </tr>
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+ <tr>
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+ <td style="text-align:center">CosyVoice</td>
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+ <td style="text-align:center">2.857</td>
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+ <td style="text-align:center"><strong>0.849</strong></td>
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+ <td style="text-align:center">4.519</td>
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+ <td style="text-align:center"><strong>0.807</strong></td>
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+ </tr>
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+ <tr>
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+ <td style="text-align:center">Step-Audio-TTS-3B</td>
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+ <td style="text-align:center"><strong>2.192</strong></td>
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+ <td style="text-align:center">0.784</td>
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+ <td style="text-align:center"><strong>3.585</strong></td>
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+ <td style="text-align:center">0.742</td>
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+ </tr>
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+ </tbody>
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+ </table>
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+ # More information
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  For more information, please refer to our repository: [Step-Audio](https://github.com/stepfun-ai/Step-Audio).