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  "Package": "chatterbox",
  "Title": "Text-to-Speech Using the 'Chatterbox' Engine",
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  "Description": "A native R 'torch' port of the 'Chatterbox' text-to-speech\nengine <https://github.com/resemble-ai/chatterbox>. Provides\nspeech synthesis with voice cloning; model weights are\ndownloaded from 'HuggingFace' <https://huggingface.co/> via the\n'hfhub' package.",
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  "Maintainer": "Troy Hernandez <troy@cornball.ai>",
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    "chatterbox",
    "chatterbox_gc_options",
    "create_voice_embedding",
    "download_chatterbox_models",
    "download_chatterbox_turbo_models",
    "generate",
    "generate_batch",
    "integrated_loudness",
    "load_chatterbox",
    "load_chatterbox_turbo",
    "load_voice_embedding",
    "models_available",
    "normalize_loudness",
    "normalize_tts_text",
    "quick_tts",
    "read_audio",
    "resample_audio",
    "s3_tokenizer",
    "save_voice_embedding",
    "serve",
    "tts_chunked",
    "tts_to_file",
    "turbo_models_available",
    "voice_convert",
    "write_audio"
  ],
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      "page": "apply_llama3_rope_scaling",
      "title": "Apply Llama3-style RoPE scaling",
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      ]
    },
    {
      "page": "apply_rotary_emb_s3",
      "title": "Apply rotary position embeddings",
      "topics": [
        "apply_rotary_emb_s3"
      ]
    },
    {
      "page": "apply_rotary_pos_emb",
      "title": "Apply rotary position embeddings to Q and K",
      "topics": [
        "apply_rotary_pos_emb"
      ]
    },
    {
      "page": "attention_block",
      "title": "Attention block for perceiver",
      "topics": [
        "attention_block"
      ]
    },
    {
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      "title": "Basic residual block for FCM",
      "topics": [
        "basic_res_block"
      ]
    },
    {
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      "title": "Basic transformer block",
      "topics": [
        "basic_transformer_block"
      ]
    },
    {
      "page": "cam_dense_tdnn_block",
      "title": "CAM Dense TDNN Block (multiple layers with dense connections)",
      "topics": [
        "cam_dense_tdnn_block"
      ]
    },
    {
      "page": "cam_dense_tdnn_layer",
      "title": "CAM Dense TDNN Layer",
      "topics": [
        "cam_dense_tdnn_layer"
      ]
    },
    {
      "page": "cam_layer",
      "title": "CAM (Context-Aware Masking) Layer",
      "topics": [
        "cam_layer"
      ]
    },
    {
      "page": "campplus",
      "title": "CAMPPlus speaker encoder",
      "topics": [
        "campplus"
      ]
    },
    {
      "page": "causal_block1d",
      "title": "Causal Block 1D - CausalConv + LayerNorm + Mish",
      "topics": [
        "causal_block1d"
      ]
    },
    {
      "page": "causal_cfm",
      "title": "Causal Conditional Flow Matching",
      "topics": [
        "causal_cfm"
      ]
    },
    {
      "page": "causal_conv1d",
      "title": "Causal Conv1d - pads left only",
      "topics": [
        "causal_conv1d"
      ]
    },
    {
      "page": "causal_masked_diff_xvec",
      "title": "Causal Masked Diff with Xvector",
      "topics": [
        "causal_masked_diff_xvec"
      ]
    },
    {
      "page": "causal_resnet_block1d",
      "title": "Causal ResNet Block 1D",
      "topics": [
        "causal_resnet_block1d"
      ]
    },
    {
      "page": "cfm_attention",
      "title": "Self-attention for transformer block",
      "topics": [
        "cfm_attention"
      ]
    },
    {
      "page": "cfm_estimator",
      "title": "CFM Estimator (ConditionalDecoder)",
      "topics": [
        "cfm_estimator"
      ]
    },
    {
      "page": "chatterbox",
      "title": "Create (and load) a Chatterbox TTS model",
      "topics": [
        "chatterbox"
      ]
    },
    {
      "page": "chatterbox_gc_options",
      "title": "Recommended torch garbage-collection settings for chatterbox",
      "topics": [
        "chatterbox_gc_options"
      ]
    },
    {
      "page": "compute_rope_frequencies",
      "title": "Compute rotary position embeddings frequencies",
      "topics": [
        "compute_rope_frequencies"
      ]
    },
    {
      "page": "compute_ve_mel",
      "title": "Compute mel spectrogram for voice encoder",
      "topics": [
        "compute_ve_mel"
      ]
    },
    {
      "page": "conformer_encoder_layer",
      "title": "Conformer Encoder Layer",
      "topics": [
        "conformer_encoder_layer"
      ]
    },
    {
      "page": "conv_rnn_f0_predictor",
      "title": "Convolutional RNN F0 Predictor",
      "topics": [
        "conv_rnn_f0_predictor"
      ]
    },
    {
      "page": "create_kv_cache",
      "title": "Create pre-allocated KV cache",
      "topics": [
        "create_kv_cache"
      ]
    },
    {
      "page": "create_mel_filterbank",
      "title": "Create mel filterbank",
      "topics": [
        "create_mel_filterbank"
      ]
    },
    {
      "page": "create_voice_embedding",
      "title": "Create voice embedding from reference audio",
      "topics": [
        "create_voice_embedding"
      ]
    },
    {
      "page": "dense_layer",
      "title": "Dense layer for final embedding",
      "topics": [
        "dense_layer"
      ]
    },
    {
      "page": "download_chatterbox_models",
      "title": "Download Chatterbox Models from HuggingFace",
      "topics": [
        "download_chatterbox_models"
      ]
    },
    {
      "page": "download_chatterbox_turbo_models",
      "title": "Download Chatterbox Turbo Models from HuggingFace",
      "topics": [
        "download_chatterbox_turbo_models"
      ]
    },
    {
      "page": "drop_invalid_tokens",
      "title": "Drop invalid speech tokens",
      "topics": [
        "drop_invalid_tokens"
      ]
    },
    {
      "page": "espnet_rel_positional_encoding",
      "title": "Sinusoidal positional encoding (Espnet RelPositionalEncoding)",
      "topics": [
        "espnet_rel_positional_encoding"
      ]
    },
    {
      "page": "fcm_module",
      "title": "Factorized Convolutional Module (FCM)",
      "topics": [
        "fcm_module"
      ]
    },
    {
      "page": "feed_forward",
      "title": "Feed-forward network for transformer Matches diffusers FeedForward: net = [GELU(proj), Dropout, Linear]",
      "topics": [
        "feed_forward"
      ]
    },
    {
      "page": "fsmn_multi_head_attention",
      "title": "FSMN Multi-Head Attention",
      "topics": [
        "fsmn_multi_head_attention"
      ]
    },
    {
      "page": "fsq_codebook",
      "title": "FSQ Codebook module",
      "topics": [
        "fsq_codebook"
      ]
    },
    {
      "page": "fsq_vector_quantization",
      "title": "FSQ Vector Quantization wrapper",
      "topics": [
        "fsq_vector_quantization"
      ]
    },
    {
      "page": "gelu_with_proj",
      "title": "GELU activation with projection (matches diffusers GELU structure)",
      "topics": [
        "gelu_with_proj"
      ]
    },
    {
      "page": "generate",
      "title": "Generate speech from text",
      "topics": [
        "generate"
      ]
    },
    {
      "page": "generate_batch",
      "title": "Generate speech for several texts with one batched synthesis pass",
      "topics": [
        "generate_batch"
      ]
    },
    {
      "page": "get_conv_padding",
      "title": "Get padding for convolution",
      "topics": [
        "get_conv_padding"
      ]
    },
    {
      "page": "get_traced_layers",
      "title": "Get or create traced layers for cached inference",
      "topics": [
        "get_traced_layers"
      ]
    },
    {
      "page": "gpt2_attention",
      "title": "GPT-2 Attention (combined QKV projection)",
      "topics": [
        "gpt2_attention"
      ]
    },
    {
      "page": "gpt2_block",
      "title": "GPT-2 Transformer Block",
      "topics": [
        "gpt2_block"
      ]
    },
    {
      "page": "gpt2_config",
      "title": "GPT-2 Model Configuration",
      "topics": [
        "gpt2_config"
      ]
    },
    {
      "page": "gpt2_layer_norm",
      "title": "GPT-2 Layer Normalization",
      "topics": [
        "gpt2_layer_norm"
      ]
    },
    {
      "page": "gpt2_mlp",
      "title": "GPT-2 MLP (GELU activation)",
      "topics": [
        "gpt2_mlp"
      ]
    },
    {
      "page": "gpt2_model",
      "title": "GPT-2 Model (transformer backbone)",
      "topics": [
        "gpt2_model"
      ]
    },
    {
      "page": "hifigan_resblock",
      "title": "HiFiGAN Residual Block",
      "topics": [
        "hifigan_resblock"
      ]
    },
    {
      "page": "hift_generator",
      "title": "HiFTNet Generator",
      "topics": [
        "hift_generator"
      ]
    },
    {
      "page": "init_cache_from_first",
      "title": "Initialize cache with first token K/V values",
      "topics": [
        "init_cache_from_first"
      ]
    },
    {
      "page": "integrated_loudness",
      "title": "Integrated loudness (ITU-R BS.1770-4)",
      "topics": [
        "integrated_loudness"
      ]
    },
    {
      "page": "is_loaded",
      "title": "Check if model is loaded",
      "topics": [
        "is_loaded"
      ]
    },
    {
      "page": "learned_position_embeddings",
      "title": "Learned position embeddings module",
      "topics": [
        "learned_position_embeddings"
      ]
    },
    {
      "page": "linear_no_subsampling",
      "title": "Linear No Subsampling layer",
      "topics": [
        "linear_no_subsampling"
      ]
    },
    {
      "page": "llama_attention",
      "title": "Llama attention module",
      "topics": [
        "llama_attention"
      ]
    },
    {
      "page": "llama_config_520m",
      "title": "Create Llama 520M configuration",
      "topics": [
        "llama_config_520m"
      ]
    },
    {
      "page": "llama_decoder_layer",
      "title": "Llama decoder layer",
      "topics": [
        "llama_decoder_layer"
      ]
    },
    {
      "page": "llama_mlp",
      "title": "Llama MLP module",
      "topics": [
        "llama_mlp"
      ]
    },
    {
      "page": "llama_model",
      "title": "Llama model (decoder only)",
      "topics": [
        "llama_model"
      ]
    },
    {
      "page": "llama_rms_norm",
      "title": "RMS Normalization module",
      "topics": [
        "llama_rms_norm"
      ]
    },
    {
      "page": "load_chatterbox",
      "title": "Load Chatterbox model weights",
      "topics": [
        "load_chatterbox"
      ]
    },
    {
      "page": "load_chatterbox_turbo",
      "title": "Load Chatterbox Turbo model weights",
      "topics": [
        "load_chatterbox_turbo"
      ]
    },
    {
      "page": "load_conformer_encoder_weights",
      "title": "Load Conformer Encoder weights",
      "topics": [
        "load_conformer_encoder_weights"
      ]
    },
    {
      "page": "load_llama_weights",
      "title": "Load weights from safetensors into Llama model",
      "topics": [
        "load_llama_weights"
      ]
    },
    {
      "page": "load_t3_turbo_weights",
      "title": "Load T3 turbo weights from safetensors",
      "topics": [
        "load_t3_turbo_weights"
      ]
    },
    {
      "page": "load_t3_weights",
      "title": "Load T3 weights from safetensors",
      "topics": [
        "load_t3_weights"
      ]
    },
    {
      "page": "load_tokenizer",
      "title": "Load tokenizer from JSON file (internal)",
      "topics": [
        "load_tokenizer"
      ]
    },
    {
      "page": "load_voice_embedding",
      "title": "Load a voice embedding from disk",
      "topics": [
        "load_voice_embedding"
      ]
    },
    {
      "page": "load_voice_encoder_weights",
      "title": "Load voice encoder weights from safetensors",
      "topics": [
        "load_voice_encoder_weights"
      ]
    },
    {
      "page": "make_non_pad_mask_s3",
      "title": "Create non-padding mask",
      "topics": [
        "make_non_pad_mask_s3"
      ]
    },
    {
      "page": "make_pad_mask",
      "title": "Create padding mask",
      "topics": [
        "make_pad_mask"
      ]
    },
    {
      "page": "mask_to_bias",
      "title": "Convert mask to attention bias",
      "topics": [
        "mask_to_bias"
      ]
    },
    {
      "page": "mish_activation",
      "title": "Mish activation",
      "topics": [
        "mish_activation"
      ]
    },
    {
      "page": "models_available",
      "title": "Check if Models are Downloaded",
      "topics": [
        "models_available"
      ]
    },
    {
      "page": "normalize_loudness",
      "title": "Normalize audio to a target loudness",
      "topics": [
        "normalize_loudness"
      ]
    },
    {
      "page": "normalize_tts_text",
      "title": "Normalize text for TTS",
      "topics": [
        "normalize_tts_text"
      ]
    },
    {
      "page": "pad_audio_for_tokenizer",
      "title": "Pad audio to multiple of token rate",
      "topics": [
        "pad_audio_for_tokenizer"
      ]
    },
    {
      "page": "perceiver_resampler",
      "title": "Perceiver resampler for conditioning compression",
      "topics": [
        "perceiver_resampler"
      ]
    },
    {
      "page": "positionwise_feedforward",
      "title": "Positionwise Feed Forward",
      "topics": [
        "positionwise_feedforward"
      ]
    },
    {
      "page": "pre_lookahead_layer",
      "title": "Pre-Lookahead Layer",
      "topics": [
        "pre_lookahead_layer"
      ]
    },
    {
      "page": "precompute_freqs_cis",
      "title": "Precompute rotary position embedding frequencies",
      "topics": [
        "precompute_freqs_cis"
      ]
    },
    {
      "page": "print.chatterbox",
      "title": "Print method for chatterbox",
      "topics": [
        "print.chatterbox"
      ]
    },
    {
      "page": "print.chatterbox_gc_options",
      "title": "Print method for chatterbox_gc_options",
      "topics": [
        "print.chatterbox_gc_options"
      ]
    },
    {
      "page": "print.voice_embedding",
      "title": "Print method for voice_embedding",
      "topics": [
        "print.voice_embedding"
      ]
    },
    {
      "page": "punc_norm",
      "title": "Normalize punctuation for TTS",
      "topics": [
        "punc_norm"
      ]
    },
    {
      "page": "quick_tts",
      "title": "Quick TTS - one-line text-to-speech",
      "topics": [
        "quick_tts"
      ]
    },
    {
      "page": "read_audio",
      "title": "Read audio file",
      "topics": [
        "read_audio"
      ]
    },
    {
      "page": "reflection_pad1d",
      "title": "Reflection padding for 1D (nn_reflection_pad1d equivalent)",
      "topics": [
        "reflection_pad1d"
      ]
    },
    {
      "page": "rel_position_attention",
      "title": "Relative Position Multi-Headed Attention",
      "topics": [
        "rel_position_attention"
      ]
    },
    {
      "page": "resample_audio",
      "title": "Resample audio",
      "topics": [
        "resample_audio"
      ]
    },
    {
      "page": "rotate_half",
      "title": "Rotate half of the tensor for RoPE",
      "topics": [
        "rotate_half"
      ]
    },
    {
      "page": "s3_audio_encoder",
      "title": "S3 Audio Encoder V2",
      "topics": [
        "s3_audio_encoder"
      ]
    },
    {
      "page": "s3_log_mel_spectrogram",
      "title": "Compute log mel spectrogram for S3Tokenizer",
      "topics": [
        "s3_log_mel_spectrogram"
      ]
    },
    {
      "page": "s3_multi_head_attention",
      "title": "Multi-Head Attention base module",
      "topics": [
        "s3_multi_head_attention"
      ]
    },
    {
      "page": "s3_residual_attention_block",
      "title": "Residual attention block",
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