Comments (4)
I have the same question. I did not find any range and description for these quality-based parameters in the repo. That would be great to add them in readme.
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Hi,
That's correct for noisiness, coloration and discontinuity. For Loudness the score represents how optimal the loudness is, that means a sample with non-optimal loudness (either too loud or too quiet) will be rated with a lower score.
Here is a brief explanation of the different dimensions:
The following graph shows the average loudness predictions of the model vs the active speech level in dBov. The optimal level is around -26 dBov because most samples in the dataset were normalized for that level (apart from the ones with non-optimal loudness on purpose).
Figure source: https://link.springer.com/book/10.1007/978-3-030-91479-0
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Hi,
For the overall quality MOS and the four quality dimensions the range is [1, 5] where 1 is poor quality and 5 is excellent quality. BTW - the quality dimensions (Noisiness, Coloration, Discontinuity, Loudness) cannot be used for synthetic speech. To predict the Naturalness of synthetic speech use the nisqa_tts.tar weights
Let me know if anything is still unclear. I'll try to add some more info to the readme or in the wiki.
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@gabrielmittag Hi, sorry to bring this up again, but I just wanted to further clarify the score when it comes to the loudness dimension. For example, if I get a 1 in loudness, does that mean the speech is too quiet, or does it mean the speech is so loud that it is peaking which is bad in a different way?
For noisiness, coloration and discontinuity I take it that we have less of each the closer to 5 we are. I.e. an audio clip that is not very noisy is closer to 5.
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Related Issues (20)
- NISQA Corpus download issue HOT 1
- Continuous metrics? HOT 4
- TTS naturalness prediction based on which model
- Could you tell me if the MOS rating is objective or subjective? HOT 4
- Full Reference or No Reference When Subjectively Rating a Speech HOT 1
- upper bound and larger bound inconsistent with step sign HOT 1
- Audio input requirements HOT 2
- pip package HOT 4
- CDUA device does not load the model HOT 2
- Interpertation of Different metrics HOT 1
- The predict result seems not reliable HOT 3
- License
- upper bound and larger bound inconsistent with step sign
- It seams slowly because of some functions running on CPU
- max window length error for most audio files HOT 1
- Utilizing finetuned weights
- mos_pred预测分数有些奇怪
- MOS prediction during runtime
- Error in loading the files using the folder name
- Why the CUDA is getting out of memory
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