Bibliographic record
Abstract
<JATS1:p>Exploring English Lyricsis the most unified collection of English art texts with transcriptions available, containing 790 unique art song selections with pronunciation as defined by the International Phonetic Alphabet (IPA). It is an invaluable resource for both the native speaking singer and singers with no previous exposure to the English language. These lyrics span nearly 500 years of art song history with texts set by more than 129 composers. Diverse segments of British, American, African American, Canadian, Scottish, Irish, and Australian cultures are represented. The scope of the lyrics selected includes works appropriate for beginners as well as those being performed by the world’s most prominent professional singers. Texts of frequently performed songs from the Royal Conservatory of Music Development Program adjudications, new composers’ collected works, as well as lyrics from major anthologies such as Joan Boytim’s First Book series are included. Detailed indications for selections that require a particular dialect or character voice pronunciation are provided. Helpful indices enable the reader to search by composer, song cycle, first line, or song title. References to settings of texts by multiple composers are indicated throughout the book. The book assists the teacher with repertoire selections while giving the student an accurate and elegant pronunciation that is ideal for intelligibility and optimal singing technique. Knowledge of the phonetic system and detailed pronunciation of new and standard repertoire are readily accessible with this text.</JATS1:p>
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; both teacher heads agree on what is shown here.
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".