feat: filter short audio segments (mic bumps) and add debug notebook

Mic bumps produce transient spikes that pass VAD onset detection but
contain no real speech — the model hallucinates "thank you" from them.
Added MIN_SPEECH_SECONDS (0.3s) filter to discard segments where the
actual speech portion is too short.

Added a Jupyter notebook (notebooks/audio_debug.ipynb) for real-time
audio visualization: streams RMS + peak amplitude into a live Plotly
FigureWidget, then provides post-hoc waveform inspection, segment
playback, and side-by-side segment comparison.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

pyproject.toml

@@ -27,3 +27,11 @@ build-backend = "hatchling.build"
 
 [tool.hatch.build.targets.wheel]
 packages = ["src/cohere_transcribe"]
+
+[dependency-groups]
+dev = [
+    "anywidget>=0.11.0",
+    "ipywidgets>=8.1.8",
+    "jupyterlab>=4.5.7",
+    "plotly>=6.7.0",
+]