soundchoice-g2p / hyperparams.yaml

flexthink

SoundChoice G2P: Initial model import

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	# Generated 2022-07-09 from:
	# /notebooks/speechbrain/recipes/LibriSpeech/G2P/hparams/hparams_g2p_rnn.yaml
	# yamllint disable
	# ################################
	# Model: LSTM (encoder) + GRU (decoder) (tokenized)
	# Authors:
	# Loren Lugosch & Mirco Ravanelli 2020
	# Artem Ploujnikov 2021
	# ################################

	# Seed needs to be set at top of yaml, before objects with parameters are made
	seed: 1234
	__set_seed: !apply:torch.manual_seed [1234]


	# Tokenizers
	char_tokenize: false
	char_token_type: unigram # ["unigram", "bpe", "char"]
	char_token_output: 512
	char_token_wordwise: true
	phn_tokenize: false
	phn_token_type: unigram # ["unigram", "bpe", "char"]
	phn_token_output: 512 # index(blank/eos/bos/unk) = 0
	phn_token_wordwise: true
	character_coverage: 1.0


	phonemes_count: 43
	graphemes_count: 31
	phonemes_enable_space: true

	# Training Parameters
	lexicon_epochs: 50
	lexicon_ctc_epochs: 10
	lexicon_limit_to_stop: 50 # No stopping by default, can override
	lexicon_limit_warmup: 50 # No stopping by default, can override
	sentence_epochs: 13
	sentence_ctc_epochs: 10
	sentence_limit_to_stop: 3
	sentence_limit_warmup: 3
	homograph_epochs: 50
	homograph_ctc_epochs: 10
	homograph_limit_to_stop: 5
	homograph_limit_warmup: 10
	lexicon_batch_size: 1024
	sentence_batch_size: 32
	homograph_batch_size: 32
	ctc_weight: 0.5
	homograph_loss_weight: 2.0
	lr: 0.002
	save_for_pretrained: true

	# Model parameters
	output_neurons: &id004 !apply:speechbrain.utils.hparams.choice

	value: false
	choices:
	true: 513
	false: 43

	enc_num_embeddings: &id005 !apply:speechbrain.utils.hparams.choice
	value: false
	choices:
	true: 513
	false: 31

	enc_dropout: 0.5
	enc_neurons: 512
	enc_num_layers: 4
	dec_dropout: 0.5
	dec_neurons: 512
	dec_att_neurons: 256
	dec_num_layers: 4
	embedding_dim: 512

	# Determines whether to use BOS (beginning-of-sequence) or EOS (end-of-sequence) tokens
	# Available modes:
	# raw: no BOS/EOS tokens are added
	# bos: a beginning-of-sequence token is added
	# eos: an end-of-sequence token is added
	grapheme_sequence_mode: bos
	phoneme_sequence_mode: bos


	# Special Token information
	bos_index: 0
	eos_index: 1
	blank_index: 2
	unk_index: 2
	token_space_index: 512


	# Language Model
	lm_emb_dim: 256 # dimension of the embeddings
	lm_rnn_size: 512 # dimension of hidden layers
	lm_layers: 2 # number of hidden layers
	lm_output_neurons: 43

	# Beam Searcher
	use_language_model: false
	beam_search_min_decode_ratio: 0
	beam_search_max_decode_ratio: 1.0
	beam_search_beam_size: 16
	beam_search_beam_size_valid: 16
	beam_search_eos_threshold: 10.0
	beam_search_using_max_attn_shift: false
	beam_search_max_attn_shift: 10
	beam_search_coverage_penalty: 5.0
	beam_search_lm_weight: 0.5
	beam_search_ctc_weight_decode: 0.4
	beam_search_temperature: 1.25
	beam_search_temperature_lm: 1.0

	# Word embeddings
	use_word_emb: true
	word_emb_model: bert-base-uncased
	word_emb_dim: 768
	word_emb_enc_dim: 256
	word_emb_norm_type: batch

	graphemes: &id028
	- A
	- B
	- C
	- D
	- E
	- F
	- G
	- H
	- I
	- J
	- K
	- L
	- M
	- N
	- O
	- P
	- Q
	- R
	- S
	- T
	- U
	- V
	- W
	- X
	- Y
	- Z
	- "'"
	- ' '

	phonemes: &id001


	- AA
	- AE
	- AH
	- AO
	- AW
	- AY
	- B
	- CH
	- D
	- DH
	- EH
	- ER
	- EY
	- F
	- G
	- HH
	- IH
	- IY
	- JH
	- K
	- L
	- M
	- N
	- NG
	- OW
	- OY
	- P
	- R
	- S
	- SH
	- T
	- TH
	- UH
	- UW
	- V
	- W
	- Y
	- Z
	- ZH
	- ' '

	enc_input_dim: &id003 !apply:speechbrain.lobes.models.g2p.model.input_dim
	use_word_emb: true
	word_emb_enc_dim: 256
	embedding_dim: 512


	phn_char_map: &id002 !apply:speechbrain.lobes.models.g2p.dataio.build_token_char_map


	# Models
	tokens: *id001
	char_phn_map: &id023 !apply:speechbrain.lobes.models.g2p.dataio.flip_map
	map_dict: *id002
	enc: &id006 !new:speechbrain.nnet.RNN.LSTM
	input_shape: [null, null, *id003]
	bidirectional: true
	hidden_size: 512
	num_layers: 4
	dropout: 0.5

	lin: &id010 !new:speechbrain.nnet.linear.Linear
	input_size: 512
	n_neurons: *id004
	bias: false

	ctc_lin: &id013 !new:speechbrain.nnet.linear.Linear
	input_size: 1024
	n_neurons: *id004
	encoder_emb: &id007 !new:speechbrain.nnet.embedding.Embedding
	num_embeddings: *id005
	embedding_dim: 512

	emb: &id008 !new:speechbrain.nnet.embedding.Embedding
	num_embeddings: *id004
	embedding_dim: 512

	dec: &id009 !new:speechbrain.nnet.RNN.AttentionalRNNDecoder
	enc_dim: 1024
	input_size: 512
	rnn_type: gru
	attn_type: content
	dropout: 0.5
	hidden_size: 512
	attn_dim: 256
	num_layers: 4

	word_emb_enc: &id012 !new:speechbrain.lobes.models.g2p.model.WordEmbeddingEncoder

	word_emb_dim: 768
	word_emb_enc_dim: 256
	norm_type: batch

	word_emb: !apply:speechbrain.lobes.models.g2p.dataio.lazy_init
	init: !name:speechbrain.wordemb.transformer.TransformerWordEmbeddings
	model: bert-base-uncased

	log_softmax: &id011 !new:speechbrain.nnet.activations.Softmax
	apply_log: true

	modules:
	model: &id014 !new:speechbrain.lobes.models.g2p.model.AttentionSeq2Seq
	enc: *id006
	encoder_emb: *id007
	emb: *id008
	dec: *id009
	lin: *id010
	out: *id011
	use_word_emb: true
	word_emb_enc: *id012
	enc: *id006
	encoder_emb: *id007
	emb: *id008
	dec: *id009
	lin: *id010
	ctc_lin: *id013
	out: *id011
	word_emb:
	word_emb_enc: *id012
	model: *id014
	lm_model: &id015 !new:speechbrain.lobes.models.RNNLM.RNNLM
	embedding_dim: 256
	rnn_layers: 2
	rnn_neurons: 512
	output_neurons: 43
	return_hidden: true

	opt_class: !name:torch.optim.Adam
	lr: 0.002

	beam_searcher: &id029 !new:speechbrain.decoders.S2SRNNBeamSearcher
	embedding: *id008
	decoder: *id009
	linear: *id010
	ctc_linear: *id013
	bos_index: 0
	eos_index: 1
	blank_index: 2
	min_decode_ratio: 0
	max_decode_ratio: 1.0
	beam_size: 16
	eos_threshold: 10.0
	using_max_attn_shift: false
	max_attn_shift: 10
	coverage_penalty: 5.0
	ctc_weight: 0.4

	beam_searcher_valid: !new:speechbrain.decoders.S2SRNNBeamSearcher
	embedding: *id008
	decoder: *id009
	linear: *id010
	ctc_linear: *id013
	bos_index: 0
	eos_index: 1
	blank_index: 2
	min_decode_ratio: 0
	max_decode_ratio: 1.0
	beam_size: 16
	eos_threshold: 10.0
	using_max_attn_shift: false
	max_attn_shift: 10
	coverage_penalty: 5.0
	ctc_weight: 0.4

	beam_searcher_lm: !new:speechbrain.decoders.seq2seq.S2SRNNBeamSearchLM
	embedding: *id008
	decoder: *id009
	linear: *id010
	ctc_linear: *id013
	language_model: *id015
	bos_index: 0
	eos_index: 1
	blank_index: 2
	min_decode_ratio: 0
	max_decode_ratio: 1.0
	beam_size: 16
	eos_threshold: 10.0
	using_max_attn_shift: false
	max_attn_shift: 10
	coverage_penalty: 5.0
	ctc_weight: 0.4
	lm_weight: 0.5
	temperature: 1.25
	temperature_lm: 1.0


	lr_annealing: &id018 !new:speechbrain.nnet.schedulers.NewBobScheduler
	initial_value: 0.002
	improvement_threshold: 0.0
	annealing_factor: 0.8
	patient: 0

	homograph_extractor: !new:speechbrain.lobes.models.g2p.homograph.SubsequenceExtractor

	seq_cost: &id016 !name:speechbrain.nnet.losses.nll_loss

	label_smoothing: 0.1

	ctc_cost: !name:speechbrain.nnet.losses.ctc_loss
	blank_index: 2

	seq_cost_metric: &id017 !name:speechbrain.nnet.losses.nll_loss

	label_smoothing: 0.1
	reduction: batch

	homograph_cost: !new:speechbrain.lobes.models.g2p.homograph.SubsequenceLoss
	seq_cost: *id016
	seq_stats: !name:speechbrain.utils.metric_stats.MetricStats
	metric: *id017
	seq_stats_homograph: !name:speechbrain.utils.metric_stats.MetricStats
	metric: *id017
	classification_stats_homograph: !name:speechbrain.utils.metric_stats.ClassificationStats

	per_stats: !name:speechbrain.utils.metric_stats.ErrorRateStats
	per_stats_homograph: !name:speechbrain.utils.metric_stats.ErrorRateStats


	model_output_keys:
	- p_seq
	- char_lens
	- encoder_out

	grapheme_encoder: &id027 !new:speechbrain.dataio.encoder.TextEncoder
	phoneme_encoder: &id024 !new:speechbrain.dataio.encoder.TextEncoder


	grapheme_tokenizer: !apply:speechbrain.lobes.models.g2p.dataio.lazy_init
	init: !name:speechbrain.tokenizers.SentencePiece.SentencePiece
	model_dir: grapheme_tokenizer
	bos_id: 0
	eos_id: 1
	unk_id: 2
	vocab_size: 512
	annotation_train: tokenizer_annotation_train.json
	annotation_read: char
	model_type: unigram # ["unigram", "bpe", "char"]
	character_coverage: 1.0
	annotation_format: json
	text_file: grapheme_annotations.txt

	phoneme_tokenizer: &id022 !apply:speechbrain.lobes.models.g2p.dataio.lazy_init
	init: !name:speechbrain.tokenizers.SentencePiece.SentencePiece
	model_dir: phoneme_tokenizer
	bos_id: 0
	eos_id: 1
	unk_id: 2
	vocab_size: 512
	annotation_train: tokenizer_annotation_train.json
	annotation_read: phn
	model_type: unigram # ["unigram", "bpe", "char"]
	character_coverage: 1.0
	annotation_list_to_check: [tokenizer_annotation_valid.json]
	annotation_format: json
	text_file: phoneme_annotations.txt

	out_phoneme_decoder_tok: &id025 !apply:speechbrain.lobes.models.g2p.dataio.char_map_detokenize
	tokenizer: *id022
	char_map: *id023
	token_space_index: 512
	wordwise: true

	out_phoneme_decoder_raw: &id026 !name:speechbrain.lobes.models.g2p.dataio.text_decode

	encoder: *id024
	out_phoneme_decoder: !apply:speechbrain.utils.hparams.choice
	value: false
	choices:
	true: *id025
	false: *id026
	encode_pipeline:
	batch: false
	use_padded_data: true
	output_keys:
	- grapheme_list
	- grapheme_encoded_list
	- grapheme_encoded
	- word_emb
	init:
	- func: !name:speechbrain.lobes.models.g2p.dataio.enable_eos_bos
	encoder: *id027
	tokens: *id028
	bos_index: 0
	eos_index: 1
	- func: !name:speechbrain.lobes.models.g2p.dataio.enable_eos_bos
	encoder: *id024
	tokens: *id001
	bos_index: 0
	eos_index: 1
	steps:
	- func: !name:speechbrain.lobes.models.g2p.dataio.clean_pipeline
	graphemes: *id028
	takes: txt
	provides: txt_cleaned
	- func: !name:speechbrain.lobes.models.g2p.dataio.grapheme_pipeline
	grapheme_encoder: *id027
	takes: txt_cleaned
	provides:
	- grapheme_list
	- grapheme_encoded_list
	- grapheme_encoded_raw

	- func: !name:speechbrain.lobes.models.g2p.dataio.add_bos_eos
	encoder: *id027
	takes: grapheme_encoded_list
	provides:
	- grapheme_encoded
	- grapheme_len
	- grapheme_encoded_eos
	- grapheme_len_eos
	- func: !name:speechbrain.lobes.models.g2p.dataio.word_emb_pipeline
	word_emb: !ref <word_emb>
	grapheme_encoder: !ref <grapheme_encoder>
	use_word_emb: !ref <use_word_emb>
	takes:
	- txt
	- grapheme_encoded
	- grapheme_len
	provides: word_emb

	decode_pipeline:
	batch: true
	output_keys:
	- phonemes
	steps:
	- func: !name:speechbrain.lobes.models.g2p.dataio.beam_search_pipeline
	beam_searcher: *id029
	takes:
	- char_lens
	- encoder_out
	provides:
	- hyps
	- scores
	- func: !apply:speechbrain.utils.hparams.choice
	value: false
	choices:
	true: !apply:speechbrain.lobes.models.g2p.dataio.char_map_detokenize
	tokenizer: *id022
	char_map: *id023
	token_space_index: 512
	wordwise: true
	false: !name:speechbrain.lobes.models.g2p.dataio.phoneme_decoder_pipeline
	phoneme_encoder: *id024
	takes:
	- hyps
	provides:
	- phonemes


	pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
	loadables:
	model: *id014
	ctc_lin: *id013