# Project Context: local-stt

## Overview
- **Project Name:** local-stt
- **Primary Goal:** Local, offline Speech-to-Text (STT) transcription of `.wav` audio files with automated punctuation and sentence-case formatting.
- **Working Directory:** `/home/openclaw/.openclaw/workspace/projects/local-stt`
- **Current Status:** In Progress (Core transcription and formatting pipeline functional).

## Environment & Dependencies
- **Interpreter:** Python 3 (Virtual environment located at `scripts/bin/python3`)
- **Key Libraries:** `sherpa-onnx`, `numpy`, `wave`, `argparse`, `re`
- **Audio Requirements:** 16kHz, mono `.wav` files.

## Models (Local ONNX)
- **STT Transducer (Offline):** `sherpa-onnx-zipformer-en-2023-06-26`
  - *Note:* Shifted from the streaming/mobile model to the standard offline fp32 Zipformer for higher accuracy and compatibility with the `OfflineRecognizer` API.
- **Punctuation Model:** `sherpa-onnx-punct-ct-transformer-zh-en-vocab272727-2024-04-12-int8`
  - *Note:* Configured using the `ct_transformer` parameter. Does not require a separate `vocab.txt` file for execution.

## Core Script: `scripts/transcribe.py`
- **Pipeline:**
  1. Loads the offline transducer and punctuation models.
  2. Reads input `.wav` via `wave` and normalizes to `float32`.
  3. Decodes the audio stream using `OfflineRecognizer`.
  4. Applies punctuation via `OfflinePunctuation` (instantiated directly, not via `from_config`).
  5. Runs a custom Python regex function (`format_sentence_case`) to convert text to lowercase, capitalize sentence starters, and capitalize the standalone pronoun "I" and its contractions.
  6. Prints the final output to the console and saves a `.txt` file to the `output/` directory matching the input filename.

## Recent Milestones & Fixes
- Resolved `RuntimeError: No graph was found in the protobuf` by matching the offline API (`OfflineRecognizer`) with the correct non-streaming Zipformer model.
- Fixed `AttributeError` for result retrieval by accessing `stream.result.text` instead of `recognizer.get_result()`.
- Corrected punctuation configuration by passing the model path to `ct_transformer` and removing the unnecessary `vocab` argument.
- Implemented a post-processing regex function to handle sentence capitalization and formatting of the raw uppercase output.
