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The task_categories "conversational" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, other
预览.
本仓库用于预览so-vits-svc-4.0训练出的各种语音模型的效果，点击角色名自动跳转对应训练参数。
推荐用谷歌浏览器，其他浏览器可能无法正确加载预览的音频。
正常说话的音色转换较为准确，歌曲包含较广的音域且bgm和声等难以去除干净，效果有所折扣。
有推荐的歌想要转换听听效果,或者其他内容建议，点我发起讨论
下面是预览音频，上下左右滑动可以看到全部
| 角色名 | 角色原声A | 被转换人声B | A音色替换B | A音色翻唱(点击直接下载) |
|---|---|---|---|---|
| 散兵 | 夢で会えたら | |||
| 胡桃 | ......... | ......... | moonlight shadow, 云烟成雨, 原点, 夢で逢えたら, 贝加尔湖畔 | |
| 神里绫华 | アムリタ, 大鱼, 遊園施設, the day you want away | |||
| 宵宫 | 昨夜书, lemon, my heart will go on, | |||
| 刻晴 | 嚣张, ファティマ, hero, | |||
| 可莉 | 樱花草, 夢をかなえてドラえもん, sun_shine, | |||
| 鹿野院平藏 | 风继续吹, 小さな恋の歌, love_yourself, | |||
| imallryt | 海阔天空, | |||
| kagami | えるの侵蝕, |
关键参数：
audio duration:训练集总时长
epoch: 轮数
其余：
batch_size = 一个step训练的片段数
segments = 音频被切分的片段
step=segments*epoch/batch_size,即模型文件后面数字由来
以散兵为例：
损失函数图像：主要看step 与 loss5，比如：
给一个大致的参考，待转换音频都为高音女生，这是较为刁钻的测试：如图，10min纯净人声，
差不多2800epoch（10000step）就已经出结果了，实际使用的是5571epoch(19500step)的文件，被训练音色和原音色相差几
何，请听上方预览音频。正常训练，10min是较为不足的训练集时长。
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