Repository Analysis

Uberi/speech_recognition

Speech recognition module for Python, supporting several engines and APIs, online and offline.

14.0 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of Uberi/speech_recognition, a Python project with 8,987 GitHub stars. SynthScan v2.0 examined 5,971 lines of code across 61 source files, recording 76 pattern matches distributed across 6 syntactic categories. The overall adjusted score of 14.0 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).

14.0
Adjusted Score
14.0
Raw Score
100%
Time Factor
2026-09-02
Last Push
9.0K
Stars
Python
Language
6.0K
Lines of Code
61
Files
76
Pattern Hits
2026-09-02
Scan Date
0.00
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

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

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 0MEDIUM 5LOW 71

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 76 distinct pattern matches across 6 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.

Hyper-Verbose Identifiers32 hits · 34 pts
SeverityFileLineSnippetContext
LOWtests/test_recognition.py20 def test_recognizer_attributes(self):CODE
LOWtests/test_audio.py133 def test_returns_self_when_already_fits(self):CODE
LOWtests/test_audio.py139 def test_raises_when_max_bytes_too_small(self):CODE
LOWtests/test_audio.py144 def test_raises_on_unaligned_frame_data(self):CODE
LOWtests/test_audio.py154 def test_raises_when_max_bytes_below_one_sample_per_width(self):CODE
LOWtests/test_audio.py174 def test_fixed_split_chunks_fit_within_max_bytes(self):CODE
LOWtests/test_audio.py191 def test_fixed_split_aligns_to_sample_boundary(self):CODE
LOWtests/test_audio.py198 def test_silence_aware_raises_setup_error_without_librosa(self):CODE
LOWtests/test_audio.py216 def test_silence_aware_translates_call_time_errors_to_setup_error(self):CODE
LOWtests/test_audio.py238 def test_silence_aware_translates_lazy_runtime_errors_to_setup_error(self):CODE
LOWtests/test_audio.py282 def test_to_float_ndarray_normalizes_each_sample_width(self):CODE
LOWtests/test_audio.py304 def test_to_float_ndarray_decodes_little_endian_regardless_of_host(self):CODE
LOWtests/test_audio.py336 def test_silence_aware_uses_single_nonsilent_range_boundary(self):CODE
LOWtests/test_audio.py368 def test_silence_aware_respects_byte_budget_strictly(self):CODE
LOWtests/test_audio.py391 def test_silence_aware_respects_byte_budget_on_realistic_audio(self):CODE
LOWtests/test_audio.py423 def test_silence_aware_snaps_to_speech_end_within_lookback(self):CODE
LOWtests/test_audio.py464 def test_silence_aware_splits_at_silence_boundary(self):CODE
LOWtests/recognizers/test_cohere_api.py12def test_transcribe_default_model(mock_client_cls):CODE
LOWtests/recognizers/test_cohere_api.py37def test_transcribe_with_language(mock_client_cls):CODE
LOWtests/recognizers/test_google_cloud.py21def test_transcribe_with_google_cloud_speech(SpeechClient):CODE
LOWtests/recognizers/test_google_cloud.py56def test_transcribe_with_specified_credentials(SpeechClient):CODE
LOWtests/recognizers/test_google_cloud.py149def test_transcribe_with_specified_api_parameters(SpeechClient):CODE
LOWtests/recognizers/test_vosk.py23def test_recognize_vosk_verbose(audio_data):CODE
LOWtests/recognizers/test_google.py68 def test_parse_without_confidence(CODE
LOWtests/recognizers/test_google.py86 def test_parse_with_confidence(CODE
LOWtests/recognizers/whisper_api/test_openai.py22def test_transcribe_with_openai_whisper(setenv_openai_api_key: None) -> None:CODE
LOWtests/recognizers/whisper_api/test_openai.py56def test_transcribe_with_gpt_transcribe(setenv_openai_api_key: None) -> None:CODE
LOWtests/recognizers/whisper_api/test_openai.py93def test_transcribe_with_specified_language(setenv_openai_api_key: None) -> None:CODE
LOWtests/recognizers/whisper_api/test_openai.py125def test_transcribe_with_specified_prompt(setenv_openai_api_key: None) -> None:CODE
LOWtests/recognizers/whisper_api/test_groq.py14def test_transcribe_with_groq_whisper(respx_mock, monkeypatch):CODE
LOWtests/recognizers/whisper_api/test_openai_compatible.py10def test_transcribe_with_openai_compatible_api(httpserver, monkeypatch):CODE
LOWspeech_recognition/__init__.py395 def snowboy_wait_for_hot_word(self, snowboy_location, snowboy_hot_word_files, source, timeout=None):CODE
Unused Imports21 hits · 20 pts
SeverityFileLineSnippetContext
LOWtests/test_audio.py203CODE
LOWtests/test_audio.py223CODE
LOWtests/test_audio.py224CODE
LOWtests/test_audio.py244CODE
LOWtests/test_audio.py274CODE
LOWtests/test_audio.py275CODE
LOWtests/recognizers/whisper_local/test_faster_whisper.py1CODE
LOWspeech_recognition/__init__.py5CODE
LOWspeech_recognition/audio.py1CODE
LOWspeech_recognition/recognizers/google_cloud.py1CODE
LOWspeech_recognition/recognizers/pocketsphinx.py1CODE
LOWspeech_recognition/recognizers/google.py1CODE
LOWspeech_recognition/recognizers/cohere_api.py1CODE
LOWspeech_recognition/recognizers/vosk.py1CODE
LOWspeech_recognition/recognizers/whisper_local/whisper.py1CODE
LOW…ecognition/recognizers/whisper_local/faster_whisper.py1CODE
LOWspeech_recognition/recognizers/whisper_local/base.py1CODE
LOWspeech_recognition/recognizers/whisper_api/groq.py1CODE
LOWspeech_recognition/recognizers/whisper_api/groq.py7CODE
LOWspeech_recognition/recognizers/whisper_api/openai.py1CODE
LOWexamples/tensorflow_commands.py4CODE
Excessive Try-Catch Wrapping10 hits · 13 pts
SeverityFileLineSnippetContext
LOWtests/test_audio.py276 except Exception as exc:CODE
LOWspeech_recognition/__init__.py153 except Exception:CODE
LOWspeech_recognition/__init__.py177 except Exception:CODE
MEDIUMspeech_recognition/__init__.py877 print('Error creating bucket %s: %s' % (bucket_name, exc))CODE
MEDIUMspeech_recognition/__init__.py896 print('Error getting job:', exc.response)CODE
LOWspeech_recognition/__init__.py929 except Exception as exc:CODE
LOWspeech_recognition/__init__.py942 except Exception as exc:CODE
MEDIUMspeech_recognition/__init__.py977 print('Error starting job:', exc.response)CODE
LOWspeech_recognition/audio.py143 except Exception as exc:CODE
LOWspeech_recognition/audio.py206 except Exception as exc:CODE
Deep Nesting9 hits · 9 pts
SeverityFileLineSnippetContext
LOWspeech_recognition/__init__.py128CODE
LOWspeech_recognition/__init__.py231CODE
LOWspeech_recognition/__init__.py466CODE
LOWspeech_recognition/__init__.py572CODE
LOWspeech_recognition/__init__.py825CODE
LOWspeech_recognition/__init__.py585CODE
LOWspeech_recognition/cli.py12CODE
LOWspeech_recognition/audio.py483CODE
LOWspeech_recognition/audio.py136CODE
Decorative Section Separators2 hits · 6 pts
SeverityFileLineSnippetContext
MEDIUMspeech_recognition/__init__.py1209# ===============================COMMENT
MEDIUMspeech_recognition/__init__.py1211# ===============================COMMENT
Modern Structural Boilerplate2 hits · 2 pts
SeverityFileLineSnippetContext
LOWspeech_recognition/recognizers/cohere_api.py9logger = logging.getLogger(__name__)CODE
LOWspeech_recognition/recognizers/whisper_api/base.py6logger = logging.getLogger(__name__)CODE