Editing Mel scale (section)

== Applications ==
The first version of [[Google]]'s [[Lyra (codec)|Lyra codec]] uses ''log mel spectrograms'' as the feature-extraction step. The transmitted data is a [[vector quantization|vector-quantized]] form of the spectrogram, which is then synthesized back to speech by a neural network. Use of the mel scale is believed to weigh the data in a way appropriate to human perception.<ref>{{cite web |title=Lyra: A New Very Low-Bitrate Codec for Speech Compression |url=https://ai.googleblog.com/2021/02/lyra-new-very-low-bitrate-codec-for.html |website=ai.googleblog.com |language=en |date=25 February 2021}} See also: {{arXiv|2102.11906}}, {{arXiv|2102.09660}}.</ref> MelGAN takes a similar approach.<ref>{{cite journal |last1=Kumar |first1=Kundan |last2=Kumar |first2=Rithesh |last3=de Boissiere |first3=Thibault |last4=Gestin |first4=Lucas |last5=Teoh |first5=Wei Zhen |last6=Sotelo |first6=Jose |last7=de Brebisson |first7=Alexandre |last8=Bengio |first8=Yoshua |last9=Courville |first9=Aaron |title=MelGAN: generative adversarial networks for conditional waveform synthesis |journal=Proceedings of the 33rd International Conference on Neural Information Processing Systems |date=8 December 2019 |pages=14910–14921 |url=https://dl.acm.org/doi/abs/10.5555/3454287.3455622 |publisher=Curran Associates Inc.}}</ref>

{{See also|Mel-frequency cepstrum#Applications}}