Prefer official Hueber transcripts over ASR; ASR as fallback only

A1.1/_template.md

@@ -24,8 +24,7 @@ Source: [ ] Course book  [ ] Workbook
 
 ## Audio / Listening
 
-Transcripts are ASR-generated (faster-whisper) unless noted otherwise —
-review for errors, especially names/numbers.
+Transcript source: [ ] Official (Hueber Transkriptionen)  [ ] ASR (faster-whisper — review for errors, especially names/numbers)
 
 ### Track [X.X] — [short description, e.g. "Anna and Ben introduce themselves"]
 ```

README.md

@@ -34,12 +34,24 @@ A1.2/                        ← added once I move on to the next book
 
 ## Audio (listening exercises)
 
-Course book audio has no printed transcript (the workbook's back section is
-the *Lösungsschlüssel* — answer key — not a transcript, so that doesn't help
-here). Raw audio files are **not** stored in this repo (see `.gitignore`);
-only their transcripts are, since that's what gives Claude context.
+Hueber (the publisher) releases official **Transkriptionen** PDFs for both
+the Kursbuch (course book) and Arbeitsbuch (workbook) — these are the
+primary source for audio content, not the *Lösungsschlüssel* (answer key,
+found at the back of the workbook, which is a different thing). Raw audio
+files are **not** stored in this repo (see `.gitignore`); only transcripts
+(text) are, since that's what gives Claude context.
 
-Workflow:
+Primary workflow — official transcripts:
+1. Get the Kursbuch and Arbeitsbuch Transkriptionen PDFs for the relevant book
+   (A1.1, A1.2, ...) — search "Menschen [level] Kursbuch/Arbeitsbuch
+   Transkriptionen pdf Hueber", or check the publisher's site.
+2. Send/upload the pages for a lesson the same way as course book/workbook
+   content — Claude extracts the per-track dialogue text into that lesson's
+   `.md` file under "Audio / Listening".
+3. No review needed for accuracy — these are publisher-official text, not ASR.
+
+Fallback workflow — local ASR (only if no official transcript exists for a
+given track, e.g. supplementary listening material):
 1. Get the audio files locally (publisher CD/app/download), any folder outside git.
 2. Run `scripts/transcribe.py` (uses `faster-whisper` on GPU) to transcribe them:
    ```bash
@@ -48,8 +60,9 @@ Workflow:
    ```
 3. Skim the `.txt` output for ASR mistakes (names, numbers, fast speech) and fix them.
 4. Reference/paste the transcript into the lesson's `.md` file under "Audio / Listening",
-   or just point at the `transcripts/lektion-XX/*.txt` path — either works, transcripts
-   are small text files so committing them is fine.
+   flagged as ASR-generated (the template already does this), or point at the
+   `transcripts/lektion-XX/*.txt` path — transcripts are small text files so
+   committing them is fine.
 
 ## Adding a new book (e.g. A1.2)