[GH-ISSUE #351] Audio buffer is not finite everywhere #173

New issue

Open

opened 2026-10-20 09:56:17 +00:00 by bsakaguchi · 11 comments

bsakaguchi commented 2026-10-20 09:56:17 +00:00

Owner

Copy link

Originally created by @xiaoshuyimei on GitHub (May 26, 2023).
Original GitHub issue: https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/issues/351

进行人声分离操作时，windows 64位系统，报错
Traceback (most recent call last):
File "D:\voiceprint_migration\RVC-beta\infer-web.py", line 294, in uvr
pre_fun.path_audio(inp_path, save_root_ins, save_root_vocal)
File "D:\voiceprint_migration\RVC-beta\infer_uvr5.py", line 135, in path_audio
wav_instrument = spec_utils.cmb_spectrogram_to_wave(
File "D:\voiceprint_migration\RVC-beta\uvr5_pack\lib_v5\spec_utils.py", line 392, in cmb_spectrogram_to_wave
wave = librosa.resample(
File "D:\voiceprint_migration\RVC-beta\runtime\lib\site-packages\librosa\util\decorators.py", line 104, in inner_f
return f(**kwargs)
File "D:\voiceprint_migration\RVC-beta\runtime\lib\site-packages\librosa\core\audio.py", line 606, in resample
util.valid_audio(y, mono=False)
File "D:\voiceprint_migration\RVC-beta\runtime\lib\site-packages\librosa\util\decorators.py", line 88, in inner_f
return f(*args, **kwargs)
File "D:\voiceprint_migration\RVC-beta\runtime\lib\site-packages\librosa\util\utils.py", line 294, in valid_audio
raise ParameterError("Audio buffer is not finite everywhere")
librosa.util.exceptions.ParameterError: Audio buffer is not finite everywhere
求助

Originally created by @xiaoshuyimei on GitHub (May 26, 2023). Original GitHub issue: https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/issues/351 进行人声分离操作时，windows 64位系统，报错 Traceback (most recent call last): File "D:\voiceprint_migration\RVC-beta\infer-web.py", line 294, in uvr pre_fun._path_audio_(inp_path, save_root_ins, save_root_vocal) File "D:\voiceprint_migration\RVC-beta\infer_uvr5.py", line 135, in _path_audio_ wav_instrument = spec_utils.cmb_spectrogram_to_wave( File "D:\voiceprint_migration\RVC-beta\uvr5_pack\lib_v5\spec_utils.py", line 392, in cmb_spectrogram_to_wave wave = librosa.resample( File "D:\voiceprint_migration\RVC-beta\runtime\lib\site-packages\librosa\util\decorators.py", line 104, in inner_f return f(**kwargs) File "D:\voiceprint_migration\RVC-beta\runtime\lib\site-packages\librosa\core\audio.py", line 606, in resample util.valid_audio(y, mono=False) File "D:\voiceprint_migration\RVC-beta\runtime\lib\site-packages\librosa\util\decorators.py", line 88, in inner_f return f(*args, **kwargs) File "D:\voiceprint_migration\RVC-beta\runtime\lib\site-packages\librosa\util\utils.py", line 294, in valid_audio raise ParameterError("Audio buffer is not finite everywhere") librosa.util.exceptions.ParameterError: Audio buffer is not finite everywhere 求助

bsakaguchi added the

help wanted

question

labels 2026-10-20 09:56:17 +00:00

bsakaguchi commented 2026-10-20 09:56:18 +00:00

Author

Owner

Copy link

@RVC-Boss commented on GitHub (May 29, 2023):

检查下你的输入的音频的路径，这个音频是不是非常短，文件很小

<!-- gh-comment-id:1566813000 --> @RVC-Boss commented on GitHub (May 29, 2023): 检查下你的输入的音频的路径，这个音频是不是非常短，文件很小

bsakaguchi commented 2026-10-20 09:56:18 +00:00

Author

Owner

Copy link

@xiaoshuyimei commented on GitHub (May 31, 2023):

音频文件我切成的都是5秒一段的，这个会是影响点吗

<!-- gh-comment-id:1569316416 --> @xiaoshuyimei commented on GitHub (May 31, 2023): 音频文件我切成的都是5秒一段的，这个会是影响点吗

bsakaguchi commented 2026-10-20 09:56:18 +00:00

Author

Owner

Copy link

@creativekoalaroo commented on GitHub (Jul 8, 2023):

Hi,
I am facing the same issue. Windows 11.
This is in the separation & reverberation removal process.
The input file name is 'toSplit.wav'. This error is consistent, tried for various different wav files (files downloaded, generated, converted from mp3, same error for all)

Is it related to the GPU or system config?
Can you please help me with this? Thanks in advance.
Please let me know if you need any further info.

toSplit.wav.reformatted.wav->Traceback (most recent call last):
File "E:\RVC\infer-web.py", line 370, in uvr
pre_fun.path_audio(
File "E:\RVC\infer_uvr5.py", line 120, in path_audio
wav_instrument = spec_utils.cmb_spectrogram_to_wave(
File "E:\RVC\uvr5_pack\lib_v5\spec_utils.py", line 392, in cmb_spectrogram_to_wave
wave = librosa.resample(
File "E:\RVC\runtime\lib\site-packages\librosa\util\decorators.py", line 104, in inner_f
return f(**kwargs)
File "E:\RVC\runtime\lib\site-packages\librosa\core\audio.py", line 576, in resample
util.valid_audio(y, mono=False)
File "E:\RVC\runtime\lib\site-packages\librosa\util\decorators.py", line 88, in inner_f
return f(*args, **kwargs)
File "E:\RVC\runtime\lib\site-packages\librosa\util\utils.py", line 294, in valid_audio
raise ParameterError("Audio buffer is not finite everywhere")
librosa.util.exceptions.ParameterError: Audio buffer is not finite everywhere

<!-- gh-comment-id:1626939931 --> @creativekoalaroo commented on GitHub (Jul 8, 2023): Hi, I am facing the same issue. Windows 11. This is in the separation & reverberation removal process. The input file name is 'toSplit.wav'. This error is consistent, tried for various different wav files (files downloaded, generated, converted from mp3, same error for all) Is it related to the GPU or system config? Can you please help me with this? Thanks in advance. Please let me know if you need any further info. ------------- toSplit.wav.reformatted.wav->Traceback (most recent call last): File "E:\RVC\infer-web.py", line 370, in uvr pre_fun._path_audio_( File "E:\RVC\infer_uvr5.py", line 120, in _path_audio_ wav_instrument = spec_utils.cmb_spectrogram_to_wave( File "E:\RVC\uvr5_pack\lib_v5\spec_utils.py", line 392, in cmb_spectrogram_to_wave wave = librosa.resample( File "E:\RVC\runtime\lib\site-packages\librosa\util\decorators.py", line 104, in inner_f return f(**kwargs) File "E:\RVC\runtime\lib\site-packages\librosa\core\audio.py", line 576, in resample util.valid_audio(y, mono=False) File "E:\RVC\runtime\lib\site-packages\librosa\util\decorators.py", line 88, in inner_f return f(*args, **kwargs) File "E:\RVC\runtime\lib\site-packages\librosa\util\utils.py", line 294, in valid_audio raise ParameterError("Audio buffer is not finite everywhere") librosa.util.exceptions.ParameterError: Audio buffer is not finite everywhere

bsakaguchi commented 2026-10-20 09:56:18 +00:00

Author

Owner

Copy link

@IndraTensei commented on GitHub (Jul 26, 2023):

Facing the same issue here too

<!-- gh-comment-id:1651854724 --> @IndraTensei commented on GitHub (Jul 26, 2023): Facing the same issue here too

bsakaguchi commented 2026-10-20 09:56:18 +00:00

Author

Owner

Copy link

@ArthurG29 commented on GitHub (Aug 11, 2023):

Hello, I am facing the same issue aswell

<!-- gh-comment-id:1674828394 --> @ArthurG29 commented on GitHub (Aug 11, 2023): Hello, I am facing the same issue aswell

bsakaguchi commented 2026-10-20 09:56:19 +00:00

Author

Owner

Copy link

@HIX4123 commented on GitHub (Oct 14, 2023):

same here too

<!-- gh-comment-id:1762763671 --> @HIX4123 commented on GitHub (Oct 14, 2023): same here too

bsakaguchi commented 2026-10-20 09:56:19 +00:00

Author

Owner

Copy link

@xiaoxor commented on GitHub (Jan 19, 2024):

I have encountered this problem as well. My GPU is a 1660ti. It has poor compatibility with half precision optimization.
. Could this be related to the issue?

<!-- gh-comment-id:1900788781 --> @xiaoxor commented on GitHub (Jan 19, 2024): I have encountered this problem as well. My GPU is a 1660ti. It has poor compatibility with half precision optimization. . Could this be related to the issue?

bsakaguchi commented 2026-10-20 09:56:19 +00:00

Author

Owner

Copy link

@Zhincore commented on GitHub (Apr 18, 2024):

Still same issue
EDIT: This was happening because I was trying to use my own script. RVC has 3 levels of try-except that re-try the _path_audio_ method again, and now I understand why 🙃 This error does not happen to me when using WebUI

<!-- gh-comment-id:2065196969 --> @Zhincore commented on GitHub (Apr 18, 2024): Still same issue EDIT: This was happening because I was trying to use my own script. RVC has 3 levels of try-except that re-try the `_path_audio_` method again, and now I understand why :upside_down_face: This error does not happen to me when using WebUI

bsakaguchi commented 2026-10-20 09:56:19 +00:00

Author

Owner

Copy link

@HaRry-qaq commented on GitHub (Jul 28, 2024):

I explored the cause.
When using the WebUI to perform operations step by step, this phenomenon rarely occurs. This may be because each time the model is re-entered, librosa is used to re-read the audio and remove possible non-compliant parts.
I use scripts to perform various operations myself. In most cases, this phenomenon does not occur. There are several possible reasons:
(1) The audio length is too short.
(2) There is complete silence in some long parts of the audio.
(3) Your graphics card may not support half-precision training.
In the above cases, before spec_utils.cmb_spectrogram_to_wave() in ./infer/modules/uvr5/vr.py, tensors such as v_spec_m will become nan. Before becoming nan, the real number domain of the complex signal of the tensor is 0.
In addition, this phenomenon often occurs in DeReverb. When this happens, commenting DeReverb can run normally.

Based on the above cases, I think that directly setting the nan value to 0 will not affect the final output. What I did was to first change nan to 0 in the cmb_spectrogram_to_wave() function in line 349 of ./infer/lib/uvr5_pack/lib_v5/spec_utils.py. So far, I have not gotten any abnormal output.

By the way, this situation may be caused by the use of librosa.core.load() in line 63 of ./infer/modules/uvr5/vr.py instead of ffmpeg. The author also gave a comment that there may be a bug there. Additionally, it is best to concatenate your training data into longer (10+ minutes) audio clips.

我探究了一下成因。
在使用WebUI分步操作时，这种现象几乎不会出现。这可能是因为每一次重新进入模型时，都会使用librosa重新读取音频，去除了可能不合规范的地方。
而我自己使用脚本执行各个操作。在大部分情况下，这个现象都不会出现。主要有以下几种可能出现的原因：
(1) 音频长度过短。
(2) 音频在某些较长的地方存在完全的静音。
(3) 你的显卡可能不支持半精度训练。
在以上情况下，在./infer/modules/uvr5/vr.py 的spec_utils.cmb_spectrogram_to_wave() 前，v_spec_m等张量都会变成nan。而在变成nan之前，张量的复数信号的实数域都是0.
此外，这种现象经常在DeReverb中出现。当出现这种情况时，注释DeReverb后能够正常运行。

由以上几种情况，我认为直接将nan值置0并不会影响最终的输出。我的做法是在./infer/lib/uvr5_pack/lib_v5/spec_utils.py 349行的cmb_spectrogram_to_wave()函数中先将nan变为0。到目前为止，我并没有得到任何异常输出。

多提一句，这种情况可能是 ./infer/modules/uvr5/vr.py 中 63 行使用了librosa.core.load()，而没有使用ffmpeg导致的，作者本人也在那里给出了可能存在bug的注释。此外，最好将训练数据拼接成较长（10分钟以上）的音频。

def cmb_spectrogram_to_wave(spec_m, mp, extra_bins_h=None, extra_bins=None):
    # 提前将nan变为0
    spec_m = np.where(np.isnan(spec_m), 0, spec_m)

    if extra_bins_h is not None:
        extra_bins_h = np.where(np.isnan(extra_bins_h), 0, extra_bins_h)
    if extra_bins is not None:
        extra_bins = np.where(np.isnan(extra_bins), 0, extra_bins)

    wave_band = {}
    bands_n = len(mp.param["band"])
    offset = 0

    for d in range(1, bands_n + 1):
        bp = mp.param["band"][d]
        # spec_s = np.ndarray(
        #     shape=(2, bp["n_fft"] // 2 + 1, spec_m.shape[2]), dtype=complex
        # )
        spec_s = np.zeros(
            shape=(2, bp["n_fft"] // 2 + 1, spec_m.shape[2]), dtype=complex
        )
        h = bp["crop_stop"] - bp["crop_start"]
        spec_s[:, bp["crop_start"] : bp["crop_stop"], :] = spec_m[
            :, offset : offset + h, :
        ]

        offset += h
        if d == bands_n:  # higher
            if extra_bins_h:  # if --high_end_process bypass
                max_bin = bp["n_fft"] // 2
                spec_s[:, max_bin - extra_bins_h : max_bin, :] = extra_bins[
                    :, :extra_bins_h, :
                ]
            if bp["hpf_start"] > 0:
                spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1)
            if bands_n == 1:
                wave = spectrogram_to_wave(
                    spec_s,
                    bp["hl"],
                    mp.param["mid_side"],
                    mp.param["mid_side_b2"],
                    mp.param["reverse"],
                )
            else:
                wave = np.add(
                    wave,
                    spectrogram_to_wave(
                        spec_s,
                        bp["hl"],
                        mp.param["mid_side"],
                        mp.param["mid_side_b2"],
                        mp.param["reverse"],
                    ),
                )
        else:
            sr = mp.param["band"][d + 1]["sr"]
            if d == 1:  # lower
                spec_s = fft_lp_filter(spec_s, bp["lpf_start"], bp["lpf_stop"])
                wave = librosa.resample(
                    spectrogram_to_wave(
                        spec_s,
                        bp["hl"],
                        mp.param["mid_side"],
                        mp.param["mid_side_b2"],
                        mp.param["reverse"],
                    ),
                    bp["sr"],
                    sr,
                    res_type="sinc_fastest",
                )
            else:  # mid
                spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1)
                spec_s = fft_lp_filter(spec_s, bp["lpf_start"], bp["lpf_stop"])
                wave2 = np.add(
                    wave,
                    spectrogram_to_wave(
                        spec_s,
                        bp["hl"],
                        mp.param["mid_side"],
                        mp.param["mid_side_b2"],
                        mp.param["reverse"],
                    ),
                )
                # wave = librosa.core.resample(wave2, bp['sr'], sr, res_type="sinc_fastest")
                wave = librosa.core.resample(wave2, bp["sr"], sr, res_type="scipy")
                # wave = librosa.core.resample(wave2, bp["sr"], sr, res_type="kaiser_best")

    return wave.T

<!-- gh-comment-id:2254544075 --> @HaRry-qaq commented on GitHub (Jul 28, 2024): I explored the cause. When using the WebUI to perform operations step by step, this phenomenon rarely occurs. This may be because each time the model is re-entered, librosa is used to re-read the audio and remove possible non-compliant parts. I use scripts to perform various operations myself. In most cases, this phenomenon does not occur. There are several possible reasons: (1) The audio length is too short. (2) There is complete silence in some long parts of the audio. (3) Your graphics card may not support half-precision training. In the above cases, before `spec_utils.cmb_spectrogram_to_wave()` in `./infer/modules/uvr5/vr.py`, tensors such as `v_spec_m` will become nan. Before becoming nan, the real number domain of the complex signal of the tensor is 0. In addition, this phenomenon often occurs in DeReverb. When this happens, commenting DeReverb can run normally. Based on the above cases, I think that directly setting the nan value to 0 will not affect the final output. What I did was to first change nan to 0 in the `cmb_spectrogram_to_wave()` function in line 349 of `./infer/lib/uvr5_pack/lib_v5/spec_utils.py`. So far, I have not gotten any abnormal output. By the way, this situation may be caused by the use of `librosa.core.load()` in line 63 of `./infer/modules/uvr5/vr.py` instead of ffmpeg. The author also gave a comment that there may be a bug there. Additionally, it is best to concatenate your training data into longer (10+ minutes) audio clips. 我探究了一下成因。 在使用WebUI分步操作时，这种现象几乎不会出现。这可能是因为每一次重新进入模型时，都会使用librosa重新读取音频，去除了可能不合规范的地方。 而我自己使用脚本执行各个操作。在大部分情况下，这个现象都不会出现。主要有以下几种可能出现的原因： (1) 音频长度过短。 (2) 音频在某些较长的地方存在完全的静音。 (3) 你的显卡可能不支持半精度训练。 在以上情况下，在`./infer/modules/uvr5/vr.py` 的`spec_utils.cmb_spectrogram_to_wave()` 前，`v_spec_m`等张量都会变成nan。而在变成nan之前，张量的复数信号的实数域都是0. 此外，这种现象经常在DeReverb中出现。当出现这种情况时，注释DeReverb后能够正常运行。 由以上几种情况，我认为直接将nan值置0并不会影响最终的输出。我的做法是在`./infer/lib/uvr5_pack/lib_v5/spec_utils.py` 349行的`cmb_spectrogram_to_wave()`函数中先将nan变为0。到目前为止，我并没有得到任何异常输出。 多提一句，这种情况可能是 `./infer/modules/uvr5/vr.py` 中 63 行使用了`librosa.core.load()`，而没有使用ffmpeg导致的，作者本人也在那里给出了可能存在bug的注释。此外，最好将训练数据拼接成较长（10分钟以上）的音频。 ```python def cmb_spectrogram_to_wave(spec_m, mp, extra_bins_h=None, extra_bins=None): # 提前将nan变为0 spec_m = np.where(np.isnan(spec_m), 0, spec_m) if extra_bins_h is not None: extra_bins_h = np.where(np.isnan(extra_bins_h), 0, extra_bins_h) if extra_bins is not None: extra_bins = np.where(np.isnan(extra_bins), 0, extra_bins) wave_band = {} bands_n = len(mp.param["band"]) offset = 0 for d in range(1, bands_n + 1): bp = mp.param["band"][d] # spec_s = np.ndarray( # shape=(2, bp["n_fft"] // 2 + 1, spec_m.shape[2]), dtype=complex # ) spec_s = np.zeros( shape=(2, bp["n_fft"] // 2 + 1, spec_m.shape[2]), dtype=complex ) h = bp["crop_stop"] - bp["crop_start"] spec_s[:, bp["crop_start"] : bp["crop_stop"], :] = spec_m[ :, offset : offset + h, : ] offset += h if d == bands_n: # higher if extra_bins_h: # if --high_end_process bypass max_bin = bp["n_fft"] // 2 spec_s[:, max_bin - extra_bins_h : max_bin, :] = extra_bins[ :, :extra_bins_h, : ] if bp["hpf_start"] > 0: spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1) if bands_n == 1: wave = spectrogram_to_wave( spec_s, bp["hl"], mp.param["mid_side"], mp.param["mid_side_b2"], mp.param["reverse"], ) else: wave = np.add( wave, spectrogram_to_wave( spec_s, bp["hl"], mp.param["mid_side"], mp.param["mid_side_b2"], mp.param["reverse"], ), ) else: sr = mp.param["band"][d + 1]["sr"] if d == 1: # lower spec_s = fft_lp_filter(spec_s, bp["lpf_start"], bp["lpf_stop"]) wave = librosa.resample( spectrogram_to_wave( spec_s, bp["hl"], mp.param["mid_side"], mp.param["mid_side_b2"], mp.param["reverse"], ), bp["sr"], sr, res_type="sinc_fastest", ) else: # mid spec_s = fft_hp_filter(spec_s, bp["hpf_start"], bp["hpf_stop"] - 1) spec_s = fft_lp_filter(spec_s, bp["lpf_start"], bp["lpf_stop"]) wave2 = np.add( wave, spectrogram_to_wave( spec_s, bp["hl"], mp.param["mid_side"], mp.param["mid_side_b2"], mp.param["reverse"], ), ) # wave = librosa.core.resample(wave2, bp['sr'], sr, res_type="sinc_fastest") wave = librosa.core.resample(wave2, bp["sr"], sr, res_type="scipy") # wave = librosa.core.resample(wave2, bp["sr"], sr, res_type="kaiser_best") return wave.T ```

bsakaguchi commented 2026-10-20 09:56:19 +00:00

Author

Owner

Copy link

@HaRry-qaq commented on GitHub (Jul 28, 2024):

@xiaoshuyimei @ArthurG29 @creativekoalaroo @Zhincore @IndraTensei

<!-- gh-comment-id:2254550949 --> @HaRry-qaq commented on GitHub (Jul 28, 2024): @xiaoshuyimei @ArthurG29 @creativekoalaroo @Zhincore @IndraTensei

bsakaguchi commented 2026-10-20 09:56:19 +00:00

Author

Owner

Copy link

@Tuanshu commented on GitHub (Nov 21, 2024):

I also encountered a similar problem. Even after ensuring that spec_m doesn't contain any None values, errors might still occur.

Later, I discovered that after spectrogram_to_wave (iFFT), None values might still be generated. So at the end of spectrogram_to_wave, I set any None values to 0.

I haven't encountered the problem since.

我也遇到類似的問題 即使確保spec_m沒有None也可能報錯
後來發現在spectrogram_to_wave (iFFT)後也可能產生None, 所以在spectrogram_to_wave 的最後將None設為0
目前沒再遇到問題

<!-- gh-comment-id:2490623133 --> @Tuanshu commented on GitHub (Nov 21, 2024): I also encountered a similar problem. Even after ensuring that `spec_m` doesn't contain any `None` values, errors might still occur. Later, I discovered that after `spectrogram_to_wave` (iFFT), None values might still be generated. So at the end of spectrogram_to_wave, I set any `None` values to 0. I haven't encountered the problem since. 我也遇到類似的問題 即使確保`spec_m`沒有`None`也可能報錯 後來發現在`spectrogram_to_wave` (iFFT)後也可能產生`None`, 所以在`spectrogram_to_wave` 的最後將`None`設為0 目前沒再遇到問題

Sign in to join this conversation.

No Branch/Tag specified

Branches Tags

main

20240604

v1

2.3.260718

2.2.231006

2.1.230814

2.0.230618

2.0.230528

1.2.230428

1.1.230416

1.0.230410

Labels

Clear labels   

AMD/Intel

  

bug

  

bug

  

bug

  

colab

  

dependencies

  

documentation

  

duplicate

  

enhancement

  

following up

  

good first issue

  

help wanted

  

invalid

  

question

  

stale

  

stale

  

stale

  

todo list

  

wontfix

No labels

AMD/Intel

bug

bug

bug

colab

dependencies

documentation

duplicate

enhancement

following up

good first issue

help wanted

invalid

question

stale

stale

stale

todo list

wontfix

Milestone

Clear milestone

No items

No milestone

Projects

Clear projects

No items

No project

Assignees

Clear assignees

No assignees

1 participant

Notifications

Subscribe

Due date

The due date is invalid or out of range. Please use the format "yyyy-mm-dd".

No due date set.

Dependencies

No dependencies set.

Reference

RVC-Project/Retrieval-based-Voice-Conversion-WebUI#173

No description provided.