N4 (NATO Native and Non Native) database
Bibliographic record
Abstract
Speech technology is covering an increasing number of languages, and systems are becoming more robust with regard to speech variability such as speaking style and accents. However, for real applications, especially in a multilingual and multinational context, further robustness to regional and even non-native accents is necessary. Among numerous corpora available for speech research few have specifically addressed this issue. The NATO Speech and Language Technology group decided to create a corpus geared towards the study of non-native accents. The group chose naval communications as the common task because it naturally includes a great deal of non-native speech and because there were training facilities where data could be collected in several countries. The N4 NATO Native and Non-Native Speech corpus was developed by the NATO research group on Speech and Language Technology in order to provide a military-oriented database for multilingual and non-native speech processing studies. Speech data was recorded in the naval transmission training centers of four countries (Germany, The Netherlands, United Kingdom, and Canada) during naval communication training sessions in 2000-2002. The material consists of native and non-native speakers using NATO Naval English procedure between ships where the typical sentence sounds like “This is alpha, whiskey, roger. I make two seven zero six hostile, two seven zero six. Out”, and reading from a text, "The North Wind and the Sun," in both English and the speaker's native language. The audio material was recorded on DAT and downsampled to 16kHz-16bit, and all the audio files have been manually transcribed and annotated with speakers identities using the Transcriber tool. Navy procedure recordings and text readings have been stored in different files. The first digit in the filename indicates the type of speech. Among speech segments, the duration of Navy procedure recordings range from 1.3 to 2.3 hours for a total of 7.5 hours. The duration of the native language text readings range from 1.5 minutes to 22.9 minutes for a total of around one hour. Canada Germany The Netherlands United Kingdom All Signal 5.30 3.20 5.00 6.30 19.80 Silence 3.00 0.56 2.00 4.70 Speech 2.30 2.64 3.00 1.60 Speech 2.30 2.64 3.00 1.60 9.54 Navy proc 2.00 1.90 2.30 1.30 Read text 0.30 0.74 0.70 0.30 Read text 0.30 0.74 0.70 0.30 2.04 Non-native 0.27 0.37 0.32 0.00 Native 0.03 0.37 0.38 0.30 The database contains the following information about each speaker: gender, age, weight, length, possible speaking or hearing disorders, education level, living area, accent, second language, the year English was learned(for non-native speakers). The speaker accents vary widely from country to country. The speaker's average age was 22.6 years. Nineteen women participated, accounting for 18% of the study participants. There were a total of 115 speakers. Canada Germany The Netherlands United Kingdom All #Speakers 22 51 31 11 115 #Women 5 0 9 5 19 Age 22-35 17-23 17-61 19-62 17-62 Age mean 28.3 20.1 21 27.5 22.6
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.048 |
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".