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Tiny Wav2letter is a tiny version of the original Wav2Letter model. It is a convolutional speech recognition neural network. This implementation was created by Arm, pruned to 50% sparsity, fine-tuned and quantized using the TensorFlow Model Optimization Toolkit.
Dataset: Fluent Speech (trianed on LibriSpeech,Mini LibrySpeech,Fluent Speech)
Please note that Fluent Speech dataset hosted on Kaggle is a licensed dataset.
Metric
Value
LER
0.0283
WER
0.089
Optimizations
Optimization
Value
Quantization
INT8
Network Inputs
Input Node Name
Shape
Description
input_1_int8
(1, 296, 39)
Speech converted to MFCCs and quantized to INT8
Network Outputs
Output Node Name
Shape
Description
Identity_int8
(1, 1, 148, 29)
A tensor of time and class probabilities, that represents the probability of each class at each timestep. Should be passed to a decoder. For example ctc_beam_search_decoder.