Statistical and Neural Network Models for Speech Recognition
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Edmondo Trentin,∗ Fabio Brugnara,∗ Yoshua Bengio,† Cesare Furlanello,∗ and Renato De Mori‡ ∗ITC-irst, Centro per la Ricerca Scientifica e Tecnologica - 38050 Pante‘ di Povo, Trento, Italy †Dept. Informatique et Recherche Ope´rationelle, Universite´ de Montre´al, Montreal, Qc, Canada, H3C-3J7 (also, AT&T Bell Labs., Holmdel, NJ, USA) ‡School of Computer Science, McGill University, Montreal, Qc, Canada, H3A2A7PROBLEM DESCRIPTION AND METHODS FOR SOLUTIONSpoken dialogue with computers is becoming a reality receiving increased attention even outside research laboratories. A collection of results obtained from research in different countries has generated valid technologies that are now used in new products. Applications in the areas of office systems (automatic call-back systems), telephone services, training, andaid to handicapped persons are now developed with more confidence than in the past.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it