TTS-E4

Voice Done

tts_e4a_jaya

Fine-tune of IndicF5 on Archival recitation (non-Vedic), 3.3 h, 3.3 h, trained on A100 40GB (Google Cloud, spot). Started 9 Oct 2026, ended 10 Oct 2026.

Hypothesis

A chant voice learned from about 3 hours of archival recitation, used with the family's permission: can a few hours of older, band-limited recordings make a clear chant voice?

What we learned

Bench letter error 0.0198, ā/a ratio 2.14; write-up pending.

Scores

Lower is better on the headline; change against the parent run, TTS-E2.

Letter error, bench
0.0198
letter error rate · headline
+171.2%
Every published score of TTS-E4, against its parent TTS-E2
Test setTTS-E4TTS-E2 (parent)Change
Letter error, bench headline
Each render is transcribed by the Su-śrotā Sanskrit speech recogniser and compared letter by letter with its text: 0.04 means 4% of letters. Mean over the bench: 30 held-out chanted verses and the bake-off's 14 verse lines. The verses' own human recordings score 0.011 on it.
0.0198 0.0073+171.2%
ā/a length ratio
How much longer a long ā lasts than a short a, by forced alignment of the known text (median, inside words). Sanskrit wants about 2: people reading measure 2.17 here; most models say long vowels too short.
2.14 2.2−2.7%
Letter error, bake-off verses
The same letter error on the bake-off's 14 verse lines only, so runs compare directly with the bake-off models.
0.0302 0.0075+302.7%

Letter error rate: the share of letters that come out wrong, as a fraction (0.0096 means 0.96% of letters): for OCR, letters read off a page; for a voice, letters a speech recogniser hears in its audio. Lower is better.

Curves

Training loss

The flow-matching loss the speech model trains on (how far its predicted sound is from the recording's), averaged over each logged stretch, by step. It falls slowly and noisily; the scores come from the bench at the end.

Model

Preset
IndicF5
Parameters
—
Layers · heads · width
22 · 16 · 1,024

Data

Recordings
Archival recitation (non-Vedic), 3.3 h, 3.3 h
Audio published
None: these voices stay internal

Compute

GPU
A100 40GB
Where
Google Cloud (spot)
Steps
15,000 / 15,000
GPU hours
4.09
Cost
$5.32
Spot restarts
2

Lineage

gcpa100spotindicf5