Listen Attend Spell Model¶
Listen Attend Spell Model¶
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class
openspeech.models.listen_attend_spell.model.
DeepCNNWithJointCTCListenAttendSpellModel
(configs: omegaconf.dictconfig.DictConfig, tokenizer: openspeech.tokenizers.tokenizer.Tokenizer)[source]¶ Listen, Attend and Spell model with configurable encoder and decoder. Paper: https://arxiv.org/abs/1508.01211
- Parameters
configs (DictConfig) – configuration set.
tokenizer (Tokenizer) – tokenizer is in charge of preparing the inputs for a model.
- Inputs:
inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be a padded FloatTensor of size
(batch, seq_length, dimension)
.input_lengths (torch.LongTensor): The length of input tensor.
(batch)
- Returns
Result of model predictions.
- Return type
outputs (dict)
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class
openspeech.models.listen_attend_spell.model.
JointCTCListenAttendSpellModel
(configs: omegaconf.dictconfig.DictConfig, tokenizer: openspeech.tokenizers.tokenizer.Tokenizer)[source]¶ Joint CTC-Attention Listen, Attend and Spell model with configurable encoder and decoder. Paper: https://arxiv.org/abs/1609.06773
- Parameters
configs (DictConfig) – configuration set.
tokenizer (Tokeizer) – tokenizer is in charge of preparing the inputs for a model.
- Inputs:
inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be a padded FloatTensor of size
(batch, seq_length, dimension)
.input_lengths (torch.LongTensor): The length of input tensor.
(batch)
- Returns
Result of model predictions.
- Return type
outputs (dict)
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class
openspeech.models.listen_attend_spell.model.
ListenAttendSpellModel
(configs: omegaconf.dictconfig.DictConfig, tokenizer: openspeech.tokenizers.tokenizer.Tokenizer)[source]¶ Listen, Attend and Spell model with configurable encoder and decoder. Paper: https://arxiv.org/abs/1508.01211
- Parameters
configs (DictConfig) – configuration set.
tokenizer (Tokeizer) – tokenizer is in charge of preparing the inputs for a model.
- Inputs:
inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be a padded FloatTensor of size
(batch, seq_length, dimension)
.input_lengths (torch.LongTensor): The length of input tensor.
(batch)
- Returns
Result of model predictions.
- Return type
outputs (dict)
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class
openspeech.models.listen_attend_spell.model.
ListenAttendSpellWithLocationAwareModel
(configs: omegaconf.dictconfig.DictConfig, tokenizer: openspeech.tokenizers.tokenizer.Tokenizer)[source]¶ Listen, Attend and Spell model with configurable encoder and decoder. Paper: https://arxiv.org/abs/1508.01211
- Parameters
configs (DictConfig) – configuration set.
tokenizer (Tokeizer) – tokenizer is in charge of preparing the inputs for a model.
- Inputs:
inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be a padded FloatTensor of size
(batch, seq_length, dimension)
.input_lengths (torch.LongTensor): The length of input tensor.
(batch)
- Returns
Result of model predictions.
- Return type
outputs (dict)
-
class
openspeech.models.listen_attend_spell.model.
ListenAttendSpellWithMultiHeadModel
(configs: omegaconf.dictconfig.DictConfig, tokenizer: openspeech.tokenizers.tokenizer.Tokenizer)[source]¶ Listen, Attend and Spell model with configurable encoder and decoder. Paper: https://arxiv.org/abs/1508.01211
- Parameters
configs (DictConfig) – configuration set.
tokenizer (Tokeizer) – tokenizer is in charge of preparing the inputs for a model.
- Inputs:
inputs (torch.FloatTensor): A input sequence passed to encoders. Typically for inputs this will be a padded FloatTensor of size
(batch, seq_length, dimension)
.input_lengths (torch.LongTensor): The length of input tensor.
(batch)
- Returns
Result of model predictions.
- Return type
outputs (dict)
Listen Attend Spell Model Configuration¶
-
class
openspeech.models.listen_attend_spell.configurations.
DeepCNNWithJointCTCListenAttendSpellConfigs
(model_name: str = 'deep_cnn_with_joint_ctc_listen_attend_spell', num_encoder_layers: int = 3, num_decoder_layers: int = 2, hidden_state_dim: int = 768, encoder_dropout_p: float = 0.3, encoder_bidirectional: bool = True, rnn_type: str = 'lstm', extractor: str = 'vgg', activation: str = 'hardtanh', joint_ctc_attention: bool = True, max_length: int = 128, num_attention_heads: int = 1, decoder_dropout_p: float = 0.2, decoder_attn_mechanism: str = 'loc', teacher_forcing_ratio: float = 1.0, optimizer: str = 'adam')[source]¶ This is the configuration class to store the configuration of a
DeepCNNWithJointCTCListenAttendSpell
.It is used to initiated an DeepCNNWithJointCTCListenAttendSpell model.
Configuration objects inherit from :class: ~openspeech.dataclass.configs.OpenspeechDataclass.
- Parameters
model_name (str) – Model name (default: deep_cnn_with_joint_ctc_listen_attend_spell)
num_encoder_layers (int) – The number of encoder layers. (default: 3)
num_decoder_layers (int) – The number of decoder layers. (default: 2)
hidden_state_dim (int) – The hidden state dimension of encoder. (default: 768)
encoder_dropout_p (float) – The dropout probability of encoder. (default: 0.3)
encoder_bidirectional (bool) – If True, becomes a bidirectional encoders (default: True)
rnn_type (str) – Type of rnn cell (rnn, lstm, gru) (default: lstm)
extractor (str) – The CNN feature extractor. (default: vgg)
activation (str) – Type of activation function (default: str)
joint_ctc_attention (bool) – Flag indication joint ctc attention or not (default: True)
max_length (int) – Max decoding length. (default: 128)
num_attention_heads (int) – The number of attention heads. (default: 1)
decoder_dropout_p (float) – The dropout probability of decoder. (default: 0.2)
decoder_attn_mechanism (str) – The attention mechanism for decoder. (default: loc)
teacher_forcing_ratio (float) – The ratio of teacher forcing. (default: 1.0)
optimizer (str) – Optimizer for training. (default: adam)
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class
openspeech.models.listen_attend_spell.configurations.
JointCTCListenAttendSpellConfigs
(model_name: str = 'joint_ctc_listen_attend_spell', num_encoder_layers: int = 3, num_decoder_layers: int = 2, hidden_state_dim: int = 768, encoder_dropout_p: float = 0.3, encoder_bidirectional: bool = True, rnn_type: str = 'lstm', joint_ctc_attention: bool = True, max_length: int = 128, num_attention_heads: int = 1, decoder_dropout_p: float = 0.2, decoder_attn_mechanism: str = 'loc', teacher_forcing_ratio: float = 1.0, optimizer: str = 'adam')[source]¶ This is the configuration class to store the configuration of a
JointCTCListenAttendSpell
.It is used to initiated an JointCTCListenAttendSpell model.
Configuration objects inherit from :class: ~openspeech.dataclass.configs.OpenspeechDataclass.
- Parameters
model_name (str) – Model name (default: joint_ctc_listen_attend_spell)
num_encoder_layers (int) – The number of encoder layers. (default: 3)
num_decoder_layers (int) – The number of decoder layers. (default: 2)
hidden_state_dim (int) – The hidden state dimension of encoder. (default: 768)
encoder_dropout_p (float) – The dropout probability of encoder. (default: 0.3)
encoder_bidirectional (bool) – If True, becomes a bidirectional encoders (default: True)
rnn_type (str) – Type of rnn cell (rnn, lstm, gru) (default: lstm)
joint_ctc_attention (bool) – Flag indication joint ctc attention or not (default: True)
max_length (int) – Max decoding length. (default: 128)
num_attention_heads (int) – The number of attention heads. (default: 1)
decoder_dropout_p (float) – The dropout probability of decoder. (default: 0.2)
decoder_attn_mechanism (str) – The attention mechanism for decoder. (default: loc)
teacher_forcing_ratio (float) – The ratio of teacher forcing. (default: 1.0)
optimizer (str) – Optimizer for training. (default: adam)
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class
openspeech.models.listen_attend_spell.configurations.
ListenAttendSpellConfigs
(model_name: str = 'listen_attend_spell', num_encoder_layers: int = 3, num_decoder_layers: int = 2, hidden_state_dim: int = 512, encoder_dropout_p: float = 0.3, encoder_bidirectional: bool = True, rnn_type: str = 'lstm', joint_ctc_attention: bool = False, max_length: int = 128, num_attention_heads: int = 1, decoder_dropout_p: float = 0.2, decoder_attn_mechanism: str = 'dot', teacher_forcing_ratio: float = 1.0, optimizer: str = 'adam')[source]¶ This is the configuration class to store the configuration of a
ListenAttendSpell
.It is used to initiated an ListenAttendSpell model.
Configuration objects inherit from :class: ~openspeech.dataclass.configs.OpenspeechDataclass.
- Parameters
model_name (str) – Model name (default: listen_attend_spell)
num_encoder_layers (int) – The number of encoder layers. (default: 3)
num_decoder_layers (int) – The number of decoder layers. (default: 2)
hidden_state_dim (int) – The hidden state dimension of encoder. (default: 512)
encoder_dropout_p (float) – The dropout probability of encoder. (default: 0.3)
encoder_bidirectional (bool) – If True, becomes a bidirectional encoders (default: True)
rnn_type (str) – Type of rnn cell (rnn, lstm, gru) (default: lstm)
joint_ctc_attention (bool) – Flag indication joint ctc attention or not (default: False)
max_length (int) – Max decoding length. (default: 128)
num_attention_heads (int) – The number of attention heads. (default: 1)
decoder_dropout_p (float) – The dropout probability of decoder. (default: 0.2)
decoder_attn_mechanism (str) – The attention mechanism for decoder. (default: dot)
teacher_forcing_ratio (float) – The ratio of teacher forcing. (default: 1.0)
optimizer (str) – Optimizer for training. (default: adam)
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class
openspeech.models.listen_attend_spell.configurations.
ListenAttendSpellWithLocationAwareConfigs
(model_name: str = 'listen_attend_spell_with_location_aware', num_encoder_layers: int = 3, num_decoder_layers: int = 2, hidden_state_dim: int = 512, encoder_dropout_p: float = 0.3, encoder_bidirectional: bool = True, rnn_type: str = 'lstm', joint_ctc_attention: bool = False, max_length: int = 128, num_attention_heads: int = 1, decoder_dropout_p: float = 0.2, decoder_attn_mechanism: str = 'loc', teacher_forcing_ratio: float = 1.0, optimizer: str = 'adam')[source]¶ This is the configuration class to store the configuration of a
ListenAttendSpellWithLocationAware
.It is used to initiated an ListenAttendSpellWithLocationAware model.
Configuration objects inherit from :class: ~openspeech.dataclass.configs.OpenspeechDataclass.
- Parameters
model_name (str) – Model name (default: listen_attend_spell_with_location_aware)
num_encoder_layers (int) – The number of encoder layers. (default: 3)
num_decoder_layers (int) – The number of decoder layers. (default: 2)
hidden_state_dim (int) – The hidden state dimension of encoder. (default: 512)
encoder_dropout_p (float) – The dropout probability of encoder. (default: 0.3)
encoder_bidirectional (bool) – If True, becomes a bidirectional encoders (default: True)
rnn_type (str) – Type of rnn cell (rnn, lstm, gru) (default: lstm)
joint_ctc_attention (bool) – Flag indication joint ctc attention or not (default: False)
max_length (int) – Max decoding length. (default: 128)
num_attention_heads (int) – The number of attention heads. (default: 1)
decoder_dropout_p (float) – The dropout probability of decoder. (default: 0.2)
decoder_attn_mechanism (str) – The attention mechanism for decoder. (default: loc)
teacher_forcing_ratio (float) – The ratio of teacher forcing. (default: 1.0)
optimizer (str) – Optimizer for training. (default: adam)
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class
openspeech.models.listen_attend_spell.configurations.
ListenAttendSpellWithMultiHeadConfigs
(model_name: str = 'listen_attend_spell_with_multi_head', num_encoder_layers: int = 3, num_decoder_layers: int = 2, hidden_state_dim: int = 512, encoder_dropout_p: float = 0.3, encoder_bidirectional: bool = True, rnn_type: str = 'lstm', joint_ctc_attention: bool = False, max_length: int = 128, num_attention_heads: int = 4, decoder_dropout_p: float = 0.2, decoder_attn_mechanism: str = 'multi-head', teacher_forcing_ratio: float = 1.0, optimizer: str = 'adam')[source]¶ This is the configuration class to store the configuration of a
ListenAttendSpellWithMultiHead
.It is used to initiated an ListenAttendSpellWithMultiHead model.
Configuration objects inherit from :class: ~openspeech.dataclass.configs.OpenspeechDataclass.
- Parameters
model_name (str) – Model name (default: listen_attend_spell_with_multi_head)
num_encoder_layers (int) – The number of encoder layers. (default: 3)
num_decoder_layers (int) – The number of decoder layers. (default: 2)
hidden_state_dim (int) – The hidden state dimension of encoder. (default: 512)
encoder_dropout_p (float) – The dropout probability of encoder. (default: 0.3)
encoder_bidirectional (bool) – If True, becomes a bidirectional encoders (default: True)
rnn_type (str) – Type of rnn cell (rnn, lstm, gru) (default: lstm)
joint_ctc_attention (bool) – Flag indication joint ctc attention or not (default: False)
max_length (int) – Max decoding length. (default: 128)
num_attention_heads (int) – The number of attention heads. (default: 4)
decoder_dropout_p (float) – The dropout probability of decoder. (default: 0.2)
decoder_attn_mechanism (str) – The attention mechanism for decoder. (default: multi-head)
teacher_forcing_ratio (float) – The ratio of teacher forcing. (default: 1.0)
optimizer (str) – Optimizer for training. (default: adam)