# Text-to-Speech Using the 'Chatterbox' Engine

## Documentation for package ‘chatterbox’ version 0.2.1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

A B C D E F G H I L M N P Q R S T U V W

## -- A --

apply_llama3_rope_scaling | Apply Llama3-style RoPE scaling
apply_rotary_emb_s3 | Apply rotary position embeddings
apply_rotary_pos_emb | Apply rotary position embeddings to Q and K
attention_block | Attention block for perceiver

## -- B --

basic_res_block | Basic residual block for FCM
basic_transformer_block | Basic transformer block

## -- C --

campplus | CAMPPlus speaker encoder
cam_dense_tdnn_block | CAM Dense TDNN Block (multiple layers with dense connections)
cam_dense_tdnn_layer | CAM Dense TDNN Layer
cam_layer | CAM (Context-Aware Masking) Layer
causal_block1d | Causal Block 1D - CausalConv + LayerNorm + Mish
causal_cfm | Causal Conditional Flow Matching
causal_conv1d | Causal Conv1d - pads left only
causal_masked_diff_xvec | Causal Masked Diff with Xvector
causal_resnet_block1d | Causal ResNet Block 1D
cfm_attention | Self-attention for transformer block
cfm_estimator | CFM Estimator (ConditionalDecoder)
chatterbox | Create (and load) a Chatterbox TTS model
chatterbox_gc_options | Recommended torch garbage-collection settings for chatterbox
compute_rope_frequencies | Compute rotary position embeddings frequencies
compute_ve_mel | Compute mel spectrogram for voice encoder
conformer_encoder_layer | Conformer Encoder Layer
conv_rnn_f0_predictor | Convolutional RNN F0 Predictor
create_kv_cache | Create pre-allocated KV cache
create_mel_filterbank | Create mel filterbank
create_voice_embedding | Create voice embedding from reference audio

## -- D --

dense_layer | Dense layer for final embedding
download_chatterbox_models | Download Chatterbox Models from HuggingFace
download_chatterbox_turbo_models | Download Chatterbox Turbo Models from HuggingFace
drop_invalid_tokens | Drop invalid speech tokens

## -- E --

espnet_rel_positional_encoding | Sinusoidal positional encoding (Espnet RelPositionalEncoding)

## -- F --

fcm_module | Factorized Convolutional Module (FCM)
feed_forward | Feed-forward network for transformer Matches diffusers FeedForward: net = [GELU(proj), Dropout, Linear]
fsmn_multi_head_attention | FSMN Multi-Head Attention
fsq_codebook | FSQ Codebook module
fsq_vector_quantization | FSQ Vector Quantization wrapper

## -- G --

gelu_with_proj | GELU activation with projection (matches diffusers GELU structure)
generate | Generate speech from text
generate_batch | Generate speech for several texts with one batched synthesis pass
get_conv_padding | Get padding for convolution
get_traced_layers | Get or create traced layers for cached inference
gpt2_attention | GPT-2 Attention (combined QKV projection)
gpt2_block | GPT-2 Transformer Block
gpt2_config | GPT-2 Model Configuration
gpt2_layer_norm | GPT-2 Layer Normalization
gpt2_mlp | GPT-2 MLP (GELU activation)
gpt2_model | GPT-2 Model (transformer backbone)

## -- H --

hifigan_resblock | HiFiGAN Residual Block
hift_generator | HiFTNet Generator

## -- I --

init_cache_from_first | Initialize cache with first token K/V values
integrated_loudness | Integrated loudness (ITU-R BS.1770-4)
is_loaded | Check if model is loaded

## -- L --

learned_position_embeddings | Learned position embeddings module
linear_no_subsampling | Linear No Subsampling layer
llama_attention | Llama attention module
llama_config_520m | Create Llama 520M configuration
llama_decoder_layer | Llama decoder layer
llama_mlp | Llama MLP module
llama_model | Llama model (decoder only)
llama_rms_norm | RMS Normalization module
load_chatterbox | Load Chatterbox model weights
load_chatterbox_turbo | Load Chatterbox Turbo model weights
load_conformer_encoder_weights | Load Conformer Encoder weights
load_llama_weights | Load weights from safetensors into Llama model
load_t3_turbo_weights | Load T3 turbo weights from safetensors
load_t3_weights | Load T3 weights from safetensors
load_tokenizer | Load tokenizer from JSON file (internal)
load_voice_embedding | Load a voice embedding from disk
load_voice_encoder_weights | Load voice encoder weights from safetensors

## -- M --

make_non_pad_mask_s3 | Create non-padding mask
make_pad_mask | Create padding mask
mask_to_bias | Convert mask to attention bias
mish_activation | Mish activation
models_available | Check if Models are Downloaded

## -- N --

normalize_loudness | Normalize audio to a target loudness
normalize_tts_text | Normalize text for TTS

## -- P --

pad_audio_for_tokenizer | Pad audio to multiple of token rate
perceiver_resampler | Perceiver resampler for conditioning compression
positionwise_feedforward | Positionwise Feed Forward
precompute_freqs_cis | Precompute rotary position embedding frequencies
pre_lookahead_layer | Pre-Lookahead Layer
print.chatterbox | Print method for chatterbox
print.chatterbox_gc_options | Print method for chatterbox_gc_options
print.voice_embedding | Print method for voice_embedding
punc_norm | Normalize punctuation for TTS

## -- Q --

quick_tts | Quick TTS - one-line text-to-speech

## -- R --

read_audio | Read audio file
reflection_pad1d | Reflection padding for 1D (nn_reflection_pad1d equivalent)
rel_position_attention | Relative Position Multi-Headed Attention
resample_audio | Resample audio
rotate_half | Rotate half of the tensor for RoPE

## -- S --

s3gen | S3Gen Token to Waveform
s3_audio_encoder | S3 Audio Encoder V2
s3_log_mel_spectrogram | Compute log mel spectrogram for S3Tokenizer
s3_multi_head_attention | Multi-Head Attention base module
s3_residual_attention_block | Residual attention block
s3_tokenizer | S3Tokenizer V2 module
s3_tokenizer_config | S3Tokenizer model configuration
save_voice_embedding | Save a voice embedding to disk
serve | Serve chatterbox over HTTP
sine_gen | Sine Generator
sinusoidal_pos_emb | Sinusoidal positional embedding for timesteps
snake_activation | Snake activation function
source_module_hn_nsf | Source Module for Neural Source Filter
statistics_pooling | Statistics pooling

## -- T --

t3_cond | Create T3 conditioning object
t3_cond_enc | T3 conditioning encoder
t3_cond_to_device | Move T3 conditioning to device
t3_config_english | Create T3 configuration (English-only)
t3_config_turbo | Create T3 turbo configuration (GPT-2 backbone)
t3_inference_traced | T3 inference with JIT tracing (optimized)
t3_model | T3 Token-to-Token TTS model
t3_model_turbo | T3 Token-to-Token TTS model (Turbo variant with GPT-2 backbone)
tdnn_layer | TDNN Layer
timestep_embedding | Timestep embedding MLP
tokenize_text | Encode text to token IDs using BPE
traceable_attention | Traceable attention module with pre-allocated KV cache
traceable_decoder_layer | Traceable decoder layer with pre-allocated KV cache
traceable_kv_projector | Traceable K/V projection module
traceable_transformer_cached | Traceable transformer for cached inference
traceable_transformer_first | Traceable transformer for first token (no cache)
transit_layer | Transit layer (channel reduction)
transpose_layer | Transpose layer for use in sequential
tts_chunked | Generate speech for long text (the long-form policy layer)
tts_to_file | Generate speech and save to file
turbo_models_available | Check if Turbo Models are Downloaded

## -- U --

update_kv_cache | Update KV cache with new K/V values
update_valid_mask | Update valid mask to include new position
upsample_1d | Upsample 1D
upsample_conformer_encoder | Upsample Conformer Encoder
upsample_conformer_encoder_full | Upsample Conformer Encoder

## -- V --

voice_convert | Convert speech to a target voice
voice_encoder | Voice encoder module
voice_encoder_config | Voice encoder configuration

## -- W --

write_audio | Write audio file