Repository Analysis

2noise/ChatTTS

A generative speech model for daily dialogue.

5.8 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of 2noise/ChatTTS, a Python project with 39,610 GitHub stars. SynthScan v2.0 examined 31,102 lines of code across 90 source files, recording 121 pattern matches distributed across 13 syntactic categories. The overall adjusted score of 5.8 places this repository in the Low 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).

5.8
Adjusted Score
5.8
Raw Score
100%
Time Factor
2026-04-10
Last Push
39.6K
Stars
Python
Language
31.1K
Lines of Code
90
Files
121
Pattern Hits
2026-07-14
Scan Date
0.09
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

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.

Severity Breakdown

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.

CRITICAL 0HIGH 8MEDIUM 12LOW 101

Directory Score Breakdown

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.

Pattern Findings

The scanner identified 121 distinct pattern matches across 13 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.

Unused Imports38 hits · 38 pts
SeverityFileLineSnippetContext
LOWtools/llm/__init__.py1CODE
LOWtools/logger/__init__.py1CODE
LOWtools/seeder/__init__.py1CODE
LOWtools/audio/__init__.py1CODE
LOWtools/audio/__init__.py2CODE
LOWtools/audio/__init__.py2CODE
LOWtools/audio/__init__.py2CODE
LOWtools/audio/__init__.py3CODE
LOWtools/audio/__init__.py4CODE
LOWtools/normalizer/__init__.py1CODE
LOWtools/normalizer/__init__.py2CODE
LOWChatTTS/__init__.py1CODE
LOWChatTTS/config/__init__.py1CODE
LOWChatTTS/utils/__init__.py1CODE
LOWChatTTS/utils/__init__.py1CODE
LOWChatTTS/utils/__init__.py2CODE
LOWChatTTS/utils/__init__.py3CODE
LOWChatTTS/utils/__init__.py3CODE
LOWChatTTS/utils/__init__.py3CODE
LOWChatTTS/utils/__init__.py3CODE
LOWChatTTS/utils/__init__.py4CODE
LOWChatTTS/utils/gpu.py6CODE
LOWChatTTS/model/__init__.py1CODE
LOWChatTTS/model/__init__.py2CODE
LOWChatTTS/model/__init__.py3CODE
LOWChatTTS/model/__init__.py4CODE
LOWChatTTS/model/__init__.py5CODE
LOWChatTTS/model/__init__.py6CODE
LOWChatTTS/model/cuda/__init__.py1CODE
LOWChatTTS/model/velocity/llm_engine.py23CODE
LOWChatTTS/model/velocity/llm_engine.py25CODE
LOWChatTTS/model/velocity/llm_engine.py31CODE
LOWChatTTS/model/velocity/__init__.py1CODE
LOWChatTTS/model/velocity/__init__.py2CODE
LOWChatTTS/model/velocity/model_loader.py9CODE
LOWexamples/web/webui.py13CODE
LOWexamples/api/openai_api.py20CODE
LOWexamples/api/postScript.py2CODE
Self-Referential Comments12 hits · 36 pts
SeverityFileLineSnippetContext
MEDIUMtools/audio/pcm.py16 # Create an in-memory byte stream bufferCOMMENT
MEDIUMChatTTS/model/velocity/llm_engine.py104 # Create the parallel GPU workers.COMMENT
MEDIUMChatTTS/model/velocity/llm_engine.py117 # Create the scheduler.COMMENT
MEDIUMChatTTS/model/velocity/llm_engine.py312 # Create the engine configs.COMMENT
MEDIUMChatTTS/model/velocity/llm_engine.py317 # Create the LLM engine.COMMENT
MEDIUMChatTTS/model/velocity/llm_engine.py354 # Create the sequences.COMMENT
MEDIUMChatTTS/model/velocity/llm_engine.py359 # Create the sequence group.COMMENT
MEDIUMChatTTS/model/velocity/llm_engine.py624 # Create the outputs.COMMENT
MEDIUMChatTTS/model/velocity/model_loader.py53 # Create a model instance.COMMENT
MEDIUMChatTTS/model/velocity/scheduler.py83 # Create the block space manager.COMMENT
MEDIUMChatTTS/model/velocity/output.py101 # Create the outputs.COMMENT
MEDIUMexamples/api/openai_api.py35# Import necessary modulesCOMMENT
Cross-Language Confusion4 hits · 20 pts
SeverityFileLineSnippetContext
HIGHexamples/cmd/run.py41 "Run: conda install -c conda-forge pynini=2.1.5 && pip install nemo_text_processing",CODE
HIGHexamples/cmd/run.py50 "Run: conda install -c conda-forge pynini=2.1.5 && pip install WeTextProcessing",CODE
HIGHexamples/web/funcs.py99 "Run: conda install -c conda-forge pynini=2.1.5 && pip install nemo_text_processing",CODE
HIGHexamples/web/funcs.py108 "Run: conda install -c conda-forge pynini=2.1.5 && pip install WeTextProcessing",CODE
Cross-File Repetition4 hits · 20 pts
SeverityFileLineSnippetContext
HIGHREADME.md0chat t t s is a text to speech model designed for dialogue applications. [uv_break]it supports mixed language input [uv_STRING
HIGHdocs/kr/README.md0chat t t s is a text to speech model designed for dialogue applications. [uv_break]it supports mixed language input [uv_STRING
HIGHdocs/cn/README.md0chat t t s is a text to speech model designed for dialogue applications. [uv_break]it supports mixed language input [uv_STRING
HIGHdocs/es/README.md0chat t t s is a text to speech model designed for dialogue applications. [uv_break]it supports mixed language input [uv_STRING
Hyper-Verbose Identifiers20 hits · 19 pts
SeverityFileLineSnippetContext
LOWChatTTS/norm.py235 def _count_invalid_characters(self, s: str):CODE
LOWChatTTS/utils/dl.py114def download_and_extract_tar_gz(CODE
LOWChatTTS/model/gpt.py164 def _prepare_generation_inputs(CODE
LOWChatTTS/model/gpt.py291 def _prepare_generation_outputs(CODE
LOWChatTTS/model/velocity/worker.py92 def profile_num_available_blocks(CODE
LOWChatTTS/model/velocity/worker.py207def _init_distributed_environment(CODE
LOWChatTTS/model/velocity/worker.py241def _check_if_gpu_supports_dtype(torch_dtype: torch.dtype):CODE
LOWChatTTS/model/velocity/configs.py203 def verify_with_parallel_config(CODE
LOWChatTTS/model/velocity/configs.py322 def verify_with_parallel_config(CODE
LOWChatTTS/model/velocity/llm_engine.py377 def get_num_unfinished_requests(self) -> int:CODE
LOWChatTTS/model/velocity/llm_engine.py385 def _check_beam_search_early_stopping(CODE
LOWChatTTS/model/velocity/llm_engine.py429 def _process_sequence_group_outputs(CODE
LOWChatTTS/model/velocity/scheduler.py127 def get_num_unfinished_seq_groups(self) -> int:CODE
LOWexamples/onnx/exporter.py137 def convert_embedding_code_cache():CODE
LOWexamples/onnx/modeling_llama.py615 def _set_gradient_checkpointing(self, module, value=False):STRING
LOWexamples/onnx/modeling_llama.py720 def _prepare_decoder_attention_mask(STRING
LOWexamples/onnx/modeling_llama.py1041 def prepare_inputs_for_generation(CODE
LOWexamples/web/funcs.py237def set_buttons_before_generate(generate_button, interrupt_button):CODE
LOWexamples/web/funcs.py249def set_buttons_after_generate(generate_button, interrupt_button, audio_output):CODE
LOWexamples/api/main.py52async def validation_exception_handler(request, exc: RequestValidationError):CODE
Deep Nesting16 hits · 16 pts
SeverityFileLineSnippetContext
LOWChatTTS/core.py66CODE
LOWChatTTS/core.py210CODE
LOWChatTTS/core.py390CODE
LOWChatTTS/utils/dl.py19CODE
LOWChatTTS/utils/io.py41CODE
LOWChatTTS/utils/gpu.py13CODE
LOWChatTTS/model/gpt.py164CODE
LOWChatTTS/model/gpt.py324CODE
LOWChatTTS/model/velocity/sequence.py35CODE
LOWChatTTS/model/velocity/llm_engine.py429CODE
LOWChatTTS/model/velocity/llm.py193CODE
LOWChatTTS/model/velocity/scheduler.py103CODE
LOWChatTTS/model/velocity/scheduler.py130CODE
LOWexamples/cmd/stream.py74CODE
LOWexamples/onnx/modeling_llama.py1121CODE
LOWexamples/web/webui.py17CODE
AI Structural Patterns13 hits · 13 pts
SeverityFileLineSnippetContext
LOWChatTTS/core.py137CODE
LOWChatTTS/core.py210CODE
LOWChatTTS/core.py278CODE
LOWChatTTS/core.py390CODE
LOWChatTTS/model/gpt.py324CODE
LOWChatTTS/model/velocity/worker.py204CODE
LOWChatTTS/model/velocity/configs.py64CODE
LOWChatTTS/model/velocity/sampling_params.py94CODE
LOWChatTTS/model/velocity/llm.py68CODE
LOWChatTTS/model/velocity/sampler.py15CODE
LOWexamples/onnx/modeling_llama.py748CODE
LOWexamples/onnx/modeling_llama.py936CODE
LOWexamples/onnx/modeling_llama.py1121CODE
Redundant / Tautological Comments5 hits · 10 pts
SeverityFileLineSnippetContext
LOWChatTTS/model/velocity/worker.py242 # Check if the GPU supports the dtype.COMMENT
LOWChatTTS/model/velocity/llm_engine.py558 # Check if we can stop the beam search.COMMENT
LOWChatTTS/model/velocity/llm_engine.py782 # Check if the sequence has reached max_model_len.COMMENT
LOWChatTTS/model/velocity/llm_engine.py787 # Check if the sequence has reached max_tokens.COMMENT
LOWChatTTS/model/velocity/llm_engine.py792 # Check if the sequence has generated the EOS token.COMMENT
Excessive Try-Catch Wrapping4 hits · 4 pts
SeverityFileLineSnippetContext
LOWChatTTS/norm.py212 except Exception as e:CODE
LOWChatTTS/model/gpt.py101 except Exception as e:CODE
LOWexamples/web/funcs.py128 except Exception as e:CODE
LOWexamples/api/openai_api.py217 except Exception as e:CODE
Over-Commented Block2 hits · 2 pts
SeverityFileLineSnippetContext
LOWChatTTS/model/velocity/llama.py1# coding=utf-8COMMENT
LOWexamples/onnx/modeling_llama.py1# coding=utf-8COMMENT
AI Slop Vocabulary1 hit · 2 pts
SeverityFileLineSnippetContext
LOWChatTTS/model/velocity/model_runner.py133 # yet. In this case, we just use a dummy slot mapping.COMMENT
Slop Phrases1 hit · 2 pts
SeverityFileLineSnippetContext
LOWChatTTS/model/velocity/configs.py590 # make sure to update docs/source/models/engine_args.rstCOMMENT
Modern Structural Boilerplate1 hit · 1 pts
SeverityFileLineSnippetContext
LOWChatTTS/model/velocity/model_runner.py95 def set_block_size(self, block_size: int) -> None:CODE