hyperparams.yaml

# ############################################################################
# Model: E2E ASR with Transformer
# Encoder: Conformer Encoder
# Decoder: Transformer Decoder + (CTC/att joint)
# Tokens: bpe
# losses: CTC + KLdiv (Label Smoothing loss)
# Authors:  Titouan Parcollet
# ############################################################################

# Feature parameters
sample_rate: 16000
n_fft: 400
n_mels: 80


####################### Model Parameters ###########################
# Transformer
d_model: 1024
nhead: 16
num_encoder_layers: 18
num_decoder_layers: 6
d_ffn: 3072
transformer_dropout: 0.1
activation: !name:torch.nn.GELU
output_neurons: 5120

# Outputs
blank_index: 3
label_smoothing: 0.1
pad_index: 0
bos_index: 1
eos_index: 2

# Decoding parameters
min_decode_ratio: 0.0
max_decode_ratio: 1.0
test_beam_size: 10
ctc_weight_decode: 0.3
scorer_beam_scale: 0.3
transformer_beam_search: True

############################## models ################################

tokenizer: !new:sentencepiece.SentencePieceProcessor

normalizer: !new:speechbrain.processing.features.InputNormalization
    norm_type: global

compute_features: !new:speechbrain.lobes.features.Fbank
    sample_rate: !ref <sample_rate>
    n_fft: !ref <n_fft>
    n_mels: !ref <n_mels>

CNN: !new:speechbrain.lobes.models.convolution.ConvolutionFrontEnd
    input_shape: (8, 10, 80)
    num_blocks: 2
    num_layers_per_block: 1
    out_channels: (64, 32)
    kernel_sizes: (3, 3)
    strides: (2, 2)
    residuals: (False, False)

Transformer: !new:speechbrain.lobes.models.transformer.TransformerASR.TransformerASR # yamllint disable-line rule:line-length
    input_size: 640
    tgt_vocab: !ref <output_neurons>
    d_model: !ref <d_model>
    nhead: !ref <nhead>
    num_encoder_layers: !ref <num_encoder_layers>
    num_decoder_layers: !ref <num_decoder_layers>
    d_ffn: !ref <d_ffn>
    dropout: !ref <transformer_dropout>
    conformer_activation: !ref <activation>
    activation: !ref <activation>
    encoder_module: conformer
    attention_type: RelPosMHAXL
    normalize_before: True
    causal: False

ctc_lin: !new:speechbrain.nnet.linear.Linear
    input_size: !ref <d_model>
    n_neurons: !ref <output_neurons>

seq_lin: !new:speechbrain.nnet.linear.Linear
    input_size: !ref <d_model>
    n_neurons: !ref <output_neurons>

asr_model: !new:torch.nn.ModuleList
    - [!ref <CNN>, !ref <Transformer>, !ref <seq_lin>, !ref <ctc_lin>]

# Scorer
ctc_scorer: !new:speechbrain.decoders.scorer.CTCScorer
    eos_index: !ref <eos_index>
    blank_index: !ref <blank_index>
    ctc_fc: !ref <ctc_lin>

scorer: !new:speechbrain.decoders.scorer.ScorerBuilder
    full_scorers: [!ref <ctc_scorer>]
    weights:
        ctc: !ref <ctc_weight_decode>
    scorer_beam_scale: !ref <scorer_beam_scale>

# We compose the inference (encoder) pipeline.
encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential
    input_shape: [null, null, !ref <n_mels>]
    compute_features: !ref <compute_features>
    normalize: !ref <normalizer>
    CNN: !ref <CNN>

decoder: !new:speechbrain.decoders.S2STransformerBeamSearcher
    modules: [!ref <Transformer>, !ref <seq_lin>]
    bos_index: !ref <bos_index>
    eos_index: !ref <eos_index>
    min_decode_ratio: !ref <min_decode_ratio>
    max_decode_ratio: !ref <max_decode_ratio>
    beam_size: !ref <test_beam_size>
    temperature: 1.15
    using_eos_threshold: True
    scorer: !ref <scorer>

modules:
    normalizer: !ref <normalizer>
    encoder: !ref <encoder>
    transformer: !ref <Transformer>
    decoder: !ref <decoder>
    ctc_lin: !ref <ctc_lin>

log_softmax: !new:torch.nn.LogSoftmax
    dim: -1

pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
    loadables:
        normalizer: !ref <normalizer>
        asr: !ref <asr_model>
        tokenizer: !ref <tokenizer>