SoTA open-source TTS
This report presents the forensic synthetic code analysis of resemble-ai/chatterbox, a Python project with 25,511 GitHub stars. SynthScan v2.0 examined 9,727 lines of code across 61 source files, recording 119 pattern matches distributed across 14 syntactic categories. The overall adjusted score of 20.4 places this repository in the Moderate AI signal band.
The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).
This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.
Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.
This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.
The scanner identified 119 distinct pattern matches across 14 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.
Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | src/chatterbox/models/s3gen/decoder.py | 244 | Forward pass of the UNet1DConditional model. Args: x: (B, 80, T) mask (_type_) | STRING |
| HIGH | src/chatterbox/models/s3gen/xvector.py | 16 | Perform padding for the list of tensors. Args: xs (List): List of Tensors [(T_1, `*`), (T_2, `*`), ..., (T_ | STRING |
| HIGH | src/chatterbox/models/s3gen/utils/mask.py | 19 | def subsequent_mask( size: int, device: torch.device = torch.device("cpu"), ) -> torch.Tensor: """C | STRING |
| HIGH | src/chatterbox/models/s3gen/utils/mask.py | 60 | Create mask for subsequent steps (size, size) with chunk size, this is for streaming encoder Args: s | STRING |
| HIGH | src/chatterbox/models/s3gen/utils/mask.py | 168 | Make mask tensor containing indices of padded part. See description of make_non_pad_mask. Args: length | STRING |
| HIGH | src/chatterbox/models/s3gen/matcha/decoder.py | 364 | Forward pass of the UNet1DConditional model. Args: x (torch.Tensor): shape (batch_size, in_channels | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | src/chatterbox/tts.py | 0 | quick cleanup func for punctuation from llms or containing chars not seen often in the dataset | STRING |
| HIGH | src/chatterbox/tts_turbo.py | 0 | quick cleanup func for punctuation from llms or containing chars not seen often in the dataset | STRING |
| HIGH | src/chatterbox/mtl_tts.py | 0 | quick cleanup func for punctuation from llms or containing chars not seen often in the dataset | STRING |
| HIGH | src/chatterbox/tts.py | 0 | conditionals for t3 and s3gen - t3 conditionals: - speaker_emb - clap_emb - cond_prompt_speech_tokens - cond_prompt_spee | STRING |
| HIGH | src/chatterbox/tts_turbo.py | 0 | conditionals for t3 and s3gen - t3 conditionals: - speaker_emb - clap_emb - cond_prompt_speech_tokens - cond_prompt_spee | STRING |
| HIGH | src/chatterbox/mtl_tts.py | 0 | conditionals for t3 and s3gen - t3 conditionals: - speaker_emb - clap_emb - cond_prompt_speech_tokens - cond_prompt_spee | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | example_tts_turbo.py | 2 | CODE | |
| LOW | src/chatterbox/__init__.py | 9 | CODE | |
| LOW | src/chatterbox/__init__.py | 10 | CODE | |
| LOW | src/chatterbox/__init__.py | 11 | CODE | |
| LOW | src/chatterbox/__init__.py | 11 | CODE | |
| LOW | src/chatterbox/models/tokenizers/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/tokenizers/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/s3tokenizer/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/s3tokenizer/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/s3tokenizer/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/s3tokenizer/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/s3tokenizer/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/t3/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/t3/t3.py | 4 | CODE | |
| LOW | src/chatterbox/models/t3/t3.py | 4 | CODE | |
| LOW | src/chatterbox/models/t3/inference/t3_hf_backend.py | 4 | CODE | |
| LOW | src/chatterbox/models/t3/modules/learned_pos_emb.py | 1 | CODE | |
| LOW | src/chatterbox/models/t3/modules/learned_pos_emb.py | 4 | CODE | |
| LOW | src/chatterbox/models/voice_encoder/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/voice_encoder/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/s3gen/__init__.py | 1 | CODE | |
| LOW | src/chatterbox/models/s3gen/__init__.py | 2 | CODE | |
| LOW | src/chatterbox/models/s3gen/flow.py | 23 | CODE | |
| LOW | src/chatterbox/models/s3gen/flow_matching.py | 14 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/chatterbox/models/t3/t3.py | 281 | speech_head=self.speech_head, | COMMENT |
| LOW | src/chatterbox/models/s3gen/decoder.py | 1 | # Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du) | COMMENT |
| LOW | src/chatterbox/models/s3gen/flow.py | 1 | # Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du) | COMMENT |
| LOW | src/chatterbox/models/s3gen/hifigan.py | 1 | # jrm: adapted from CosyVoice/cosyvoice/hifigan/generator.py | COMMENT |
| LOW | src/chatterbox/models/s3gen/f0_predictor.py | 1 | # Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Kai Hu) | COMMENT |
| LOW | src/chatterbox/models/s3gen/s3gen.py | 1 | # Modified from CosyVoice https://github.com/FunAudioLLM/CosyVoice | COMMENT |
| LOW | src/chatterbox/models/s3gen/flow_matching.py | 1 | # Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu, Zhihao Du) | COMMENT |
| LOW | src/chatterbox/models/s3gen/transformer/attention.py | 1 | # Copyright (c) 2019 Shigeki Karita | COMMENT |
| LOW | src/chatterbox/models/s3gen/transformer/attention.py | 161 | Returns: | COMMENT |
| LOW | src/chatterbox/models/s3gen/transformer/attention.py | 281 | # cache(1, head, 0, d_k * 2) (16/-1, -1/-1, 16/0 mode) | COMMENT |
| LOW | src/chatterbox/models/s3gen/transformer/subsampling.py | 1 | # Copyright (c) 2021 Mobvoi Inc (Binbin Zhang, Di Wu) | COMMENT |
| LOW | src/chatterbox/models/s3gen/transformer/convolution.py | 1 | # Copyright (c) 2020 Mobvoi Inc. (authors: Binbin Zhang, Di Wu) | COMMENT |
| LOW | …hatterbox/models/s3gen/transformer/upsample_encoder.py | 1 | # Copyright (c) 2021 Mobvoi Inc (Binbin Zhang, Di Wu) | COMMENT |
| LOW | src/chatterbox/models/s3gen/transformer/embedding.py | 1 | # Copyright (c) 2020 Mobvoi Inc. (authors: Binbin Zhang, Di Wu) | COMMENT |
| LOW | …c/chatterbox/models/s3gen/transformer/encoder_layer.py | 1 | # Copyright (c) 2021 Mobvoi Inc (Binbin Zhang, Di Wu) | COMMENT |
| LOW | src/chatterbox/models/s3gen/transformer/activation.py | 1 | # Copyright (c) 2020 Johns Hopkins University (Shinji Watanabe) | COMMENT |
| LOW | …/models/s3gen/transformer/positionwise_feed_forward.py | 1 | # Copyright (c) 2019 Shigeki Karita | COMMENT |
| LOW | src/chatterbox/models/s3gen/utils/class_utils.py | 1 | # Copyright [2023-11-28] <sxc19@mails.tsinghua.edu.cn, Xingchen Song> | COMMENT |
| LOW | src/chatterbox/models/s3gen/utils/mask.py | 1 | # Copyright (c) 2019 Shigeki Karita | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 63 | CODE | |
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 64 | CODE | |
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 66 | CODE | |
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 69 | CODE | |
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 70 | CODE | |
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 71 | CODE | |
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 73 | CODE | |
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 74 | CODE | |
| MEDIUM | src/chatterbox/models/s3gen/flow_matching.py | 76 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/chatterbox/tts_turbo.py | 248 | CODE | |
| LOW | src/chatterbox/models/t3/t3.py | 226 | CODE | |
| LOW | src/chatterbox/models/s3gen/decoder.py | 100 | CODE | |
| LOW | src/chatterbox/models/s3gen/flow.py | 44 | CODE | |
| LOW | src/chatterbox/models/s3gen/hifigan.py | 291 | CODE | |
| LOW | src/chatterbox/models/s3gen/xvector.py | 91 | CODE | |
| LOW | src/chatterbox/models/s3gen/xvector.py | 127 | CODE | |
| LOW | src/chatterbox/models/s3gen/xvector.py | 341 | CODE | |
| LOW | …hatterbox/models/s3gen/transformer/upsample_encoder.py | 101 | CODE | |
| LOW | src/chatterbox/models/s3gen/utils/mask.py | 86 | CODE | |
| LOW | src/chatterbox/models/s3gen/utils/mel.py | 21 | CODE | |
| LOW | src/chatterbox/models/s3gen/utils/mel.py | 36 | CODE | |
| LOW | src/chatterbox/models/s3gen/matcha/decoder.py | 61 | CODE | |
| LOW | src/chatterbox/models/s3gen/matcha/decoder.py | 162 | CODE | |
| LOW | src/chatterbox/models/s3gen/matcha/decoder.py | 201 | CODE | |
| LOW | src/chatterbox/models/s3gen/matcha/transformer.py | 159 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | gradio_tts_turbo_app.py | 62 | if (end < current_text.length && current_text[end] === ' ') suffix = ""; | CODE |
| HIGH | gradio_tts_app.py | 61 | min_p = gr.Slider(0.00, 1.00, step=0.01, label="min_p || Newer Sampler. Recommend 0.02 > 0.1. Handles Hi | CODE |
| HIGH | gradio_tts_app.py | 62 | top_p = gr.Slider(0.00, 1.00, step=0.01, label="top_p || Original Sampler. 1.0 Disables(recommended). Or | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | multilingual_app.py | 150 | except Exception as e: | CODE |
| MEDIUM⚡ | multilingual_app.py | 151 | print(f"Error loading model: {e}") | CODE |
| LOW⚡ | multilingual_app.py | 158 | except Exception as e: | CODE |
| LOW | src/chatterbox/tts_turbo.py | 212 | except Exception as e: | CODE |
| MEDIUM | src/chatterbox/tts_turbo.py | 204 | def norm_loudness(self, wav, sr, target_lufs=-27): | CODE |
| LOW | src/chatterbox/models/tokenizers/tokenizer.py | 131 | except Exception as e: | CODE |
| LOW | src/chatterbox/models/tokenizers/tokenizer.py | 187 | except Exception as e: | CODE |
| LOW | src/chatterbox/models/tokenizers/tokenizer.py | 251 | except Exception as e: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | README.md | 43 | | **Chatterbox-Multilingual V3** [(Language list)](#supported-languages) | **50 | CODE |
| MEDIUM | README.md | 45 | | Chatterbox [(Tips and Tricks)](#original-chatterbox-tips) | 500M | CODE |
| MEDIUM | src/chatterbox/models/s3gen/s3gen.py | 343 | # hallucination prevention, drop special tokens | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/chatterbox/tts_turbo.py | 24 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/chatterbox/models/tokenizers/tokenizer.py | 18 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/chatterbox/models/t3/t3.py | 6 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/chatterbox/models/t3/t3.py | 30 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/chatterbox/models/s3gen/flow.py | 18 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/chatterbox/models/s3gen/flow.py | 27 | logger = logging.getLogger(__name__) | CODE |
| LOW | src/chatterbox/models/s3gen/utils/mel.py | 7 | logger = logging.getLogger(__name__) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/chatterbox/models/tokenizers/tokenizer.py | 75 | CODE | |
| LOW | src/chatterbox/models/tokenizers/tokenizer.py | 285 | CODE | |
| LOW | src/chatterbox/models/s3gen/decoder.py | 229 | CODE | |
| LOW | src/chatterbox/models/s3gen/xvector.py | 130 | CODE | |
| LOW | src/chatterbox/models/s3gen/utils/mask.py | 89 | CODE | |
| LOW | src/chatterbox/models/s3gen/matcha/decoder.py | 345 | CODE | |
| LOW | src/chatterbox/models/s3gen/matcha/transformer.py | 96 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | multilingual_app.py | 120 | def get_supported_languages_display() -> str: | CODE |
| LOW | src/chatterbox/models/t3/inference/t3_hf_backend.py | 34 | def prepare_inputs_for_generation( | CODE |
| LOW | src/chatterbox/models/t3/modules/perceiver.py | 22 | def _relative_position_bucket(relative_position, causal=True, num_buckets=32, max_distance=128): | CODE |
| LOW | src/chatterbox/models/t3/modules/perceiver.py | 84 | def scaled_dot_product_attention(self, q, k, v, mask=None): | CODE |
| LOW | src/chatterbox/models/s3gen/utils/mel.py | 15 | def dynamic_range_compression_torch(x, C=1, clip_val=1e-5): | CODE |
| LOW | src/chatterbox/models/s3gen/utils/intmeanflow.py | 5 | def get_intmeanflow_time_mixer(dims): | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/chatterbox/vc.py | 63 | # Check if MPS is available on macOS | COMMENT |
| LOW | src/chatterbox/tts.py | 169 | # Check if MPS is available on macOS | COMMENT |
| LOW | src/chatterbox/tts_turbo.py | 187 | # Check if MPS is available on macOS | COMMENT |
| LOW | src/chatterbox/mtl_tts.py | 233 | # Check if MPS is available on macOS | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | src/chatterbox/models/s3gen/transformer/convolution.py | 124 | # It's better we just return None if no cache is required, | COMMENT |