Bibliographic record
Abstract
The French-Canadian Speecon database is divided into 2 sets: 1) The first set comprises the recordings of 550 adult French-Canadian speakers (276 males, 274 females), recorded over 4 microphone channels in 4 recording environments (office, entertainment, car, public place). 2) The second set comprises the recordings of 50 child French-Canadian speakers (20 boys, 30 girls), recorded over 4 microphone channels in 1 recording environment (children room). This database is partitioned into 29 DVDs (first set) and 4 DVDs (second set).The speech databases made within the Speecon project were validated by SPEX, the Netherlands, to assess their compliance with the Speecon format and content specifications. Each of the four speech channels is recorded at 16 kHz, 16 bit, uncompressed unsigned integers in Intel format (lo-hi byte order). To each signal file corresponds an ASCII SAM label file which contains the relevant descriptive information.Each speaker uttered the following items (over 290 items for adults and over 210 items for children):Calibration data: - 6 noise recordings - The “silence word” recordingFree spontaneous items (adults only):- 5 minutes (session time) of free spontaneous, rich context items (story telling) (an open number of spontaneous topics out of a set of 30 topics)- 17 Elicited spontaneous items (adults only):- 3 dates, 2 times, 3 proper names, 2 city names, 1 letter sequence, 2 answers to questions, 3 telephone numbers, 1 language Read speech:- 30 phonetically rich sentences uttered by adults and 60 uttered by children- 5 phonetically rich words (adults only)- 4 isolated digits- 1 isolated digit sequence- 4 connected digit sequences- 1 telephone number- 3 natural numbers- 1 money amount- 2 time phrases (T1 : analogue, T2 : digital)- 3 dates (D1 : analogue, D2 : relative and general date, D3 : digital)- 3 letter sequences- 1 proper name- 2 city or street names- 2 questions- 2 special keyboard characters - 1 Web address- 1 email address- 213 application specific words and phrases per session (adults)- 74 toy commands, 14 phone commands and 34 general commands (children)The following age distribution has been obtained: - Adults: 220 speakers are between 15 and 30, 226 speakers are between 31 and 45, 104 speakers are over 46.- Children: 24 speakers are between 8 and 10, and 26 speakers are between 11 and 15.A pronunciation lexicon with a phonemic transcription in SAMPA is also included.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.133 | 0.072 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".