Comments (3)
The codec has been trained on thousands of hours of speech in more than 70 languages and tested on many different speakers and accents. It relies only on log-mel spectrograms per frame and no long-term speaker id. For some audio samples you can check out our blog or generate them yourself using encoder_main and decoder_main.
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The codec has been trained on thousands of hours of speech in more than 70 languages and tested on many different speakers and accents. It relies only on log-mel spectrograms per frame and no long-term speaker id. For some audio samples you can check out our blog or generate them yourself using encoder_main and decoder_main.
Did the training data including 70 languages as you said contain Chinese speech data? If it did, what is the proportion of Chinese speech data?
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Our training data definitely contained Chinese speech data. But since we combined several different datasets it is difficult to estimate the precise proportion. Please see reply in #32.
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Related Issues (20)
- MacOS 13.0.1 build: symbol not found in flat namespace '_CFRelease'
- the problem about building v0.0.2 version
- bazel build -c opt lyra/cli_example:encoder_main error on 20.04-Ubuntu
- Can't we directly encode pcm? HOT 3
- Noisy audio
- Can the model size be cut? HOT 1
- Is there any plan to make this lib work on older android devices? HOT 2
- Linux build HOT 1
- ANDROID BUILD HOT 1
- Can't load TFLite output_details for quantizer model (encode) HOT 3
- When will lyra support ios platform? HOT 1
- The decoding CPU is too high. Is there any way to reduce it?
- model structure of lyra 1.3.2
- About crash problem with kInternalSampleRateHz set to 32k
- Android app built as per readme crashes (on Samsung S23) HOT 1
- how to read the encoded data in the sample1_16kHz.lyra file into python/numpy array?
- Directly provide the executable download address HOT 3
- Is that possible to release the model coeffs with codebook size=1024?
- Is it possible to still run the V1 model with the latest API? Or only V2
- LMCodec HOT 2
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