| """Text helpers shared by the voice-study scripts. |
| |
| Copied verbatim from the stimulus-generation code, which is not part of the |
| release. |
| """ |
|
|
| from __future__ import annotations |
|
|
| import re |
|
|
| HIST_SPLIT = re.compile(r"role: (user|model)\\n response: ") |
|
|
|
|
| def normalize(text: str) -> list[str]: |
| text = text.lower() |
| text = re.sub(r"[^a-z0-9' ]+", " ", text) |
| return text.split() |
|
|
|
|
| def wer(ref: list[str], hyp: list[str]) -> float: |
| """Standard word error rate via edit distance.""" |
| d = list(range(len(hyp) + 1)) |
| for i, r in enumerate(ref, 1): |
| prev, d[0] = d[0], i |
| for j, h in enumerate(hyp, 1): |
| cur = min(d[j] + 1, d[j - 1] + 1, prev + (r != h)) |
| prev, d[j] = d[j], cur |
| return d[-1] / max(1, len(ref)) |
|
|
|
|
| def parse_history(prev_hist: str) -> list[tuple[str, str]]: |
| """-> [(role, text), ...] in order; identical logic to the survey page.""" |
| parts = [p for p in HIST_SPLIT.split(prev_hist)] |
| turns, i = [], 0 |
| |
| while i + 1 < len(parts): |
| if parts[i] in ("user", "model") and parts[i + 1].strip(): |
| turns.append((parts[i], parts[i + 1].strip())) |
| i += 2 |
| else: |
| i += 1 |
| return turns |
|
|
