Comments (6)
Thank you for the feedback. With the current implementation the decoder is expected to be much slower than the encoder, since the encoder only has to extract the features, but the decoder runs the expensive generative model to recreate the time domain signal from the features.
from lyra.
Is there has any plan to improve decoder performance?
from lyra.
Yes, absolutely, we are currently working on reducing computational complexity of the decoder.
from lyra.
I find that the decoder consume 50ms with one frame(40ms) and opus decoder is 0.3ms, it that right?
from lyra.
It is highly dependent on the architecture. Our matrix multiplication libraries are optimized for arm64 devices and for medium-end phones Lyra should be at least 4x faster than real-time. But that is still slower than Opus.
from lyra.
The new Lyra 1.2.0 release is about 5x faster than the previous version. And moreover, now the encoder and decoder have similar complexities.
from lyra.
Related Issues (20)
- 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
- Build fails on MacOS due to bad Tensorflow link HOT 1
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from lyra.