vad : add initial Voice Activity Detection (VAD) support (#3065)

* vad : add initial Voice Activity Detection (VAD) support

This commit add support for Voice Activity Detection (VAD). When enabled
this feature will process the audio input and detect speech segments.
This information is then used to reduce the number of samples that need
to be processed by whisper_full.

Resolves: https://github.com/ggml-org/whisper.cpp/issues/3003

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

README.md

@@ -25,6 +25,7 @@ High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisp
 - [Ascend NPU Support](#ascend-npu-support)
 - [Moore Threads GPU Support](#moore-threads-gpu-support)
 - [C-style API](https://github.com/ggml-org/whisper.cpp/blob/master/include/whisper.h)
+- [Voice Activity Detection (VAD)](#voice-activity-detection-vad)
 
 Supported platforms:
 
@@ -732,6 +733,64 @@ let package = Package(
 )
 ```
 
+### Voice Activity Detection (VAD)
+Support for Voice Activity Detection (VAD) can be enabled using the `--vad`
+argument to `whisper-cli`. In addition to this option a VAD model is also
+required.
+
+The way this works is that first the audio samples are passed through
+the VAD model which will detect speech segments. Using this information the
+only the speech segments that are detected are extracted from the original audio
+input and passed to whisper for processing. This reduces the amount of audio
+data that needs to be processed by whisper and can significantly speed up the
+transcription process.
+
+The following VAD models are currently supported:
+
+#### Silero-VAD
+[Silero-vad](https://github.com/snakers4/silero-vad) is a lightweight VAD model
+written in Python that is fast and accurate.
+
+This model can be converted to ggml using the following command:
+```console
+$ python3 -m venv venv && source venv/bin/activate
+$ (venv) pip install silero-vad
+$ (venv) $ python models/convert-silero-vad-to-ggml.py --output models/silero.bin
+Saving GGML Silero-VAD model to models/silero-v5.1.2-ggml.bin
+```
+And it can then be used with whisper as follows:
+```console
+$ ./build/bin/whisper-cli \
+   --file ./samples/jfk.wav \
+   --model ./models/ggml-base.en.bin \
+   --vad \
+   --vad-model ./models/silero-v5.1.2-ggml.bin
+```
+
+#### VAD Options
+
+* --vad-threshold: Threshold probability for speech detection. A probability
+for a speech segment/frame above this threshold will be considered as speech.
+
+* --vad-min-speech-duration-ms: Minimum speech duration in milliseconds. Speech
+segments shorter than this value will be discarded to filter out brief noise or
+false positives.
+
+* --vad-min-silence-duration-ms: Minimum silence duration in milliseconds. Silence
+periods must be at least this long to end a speech segment. Shorter silence
+periods will be ignored and included as part of the speech.
+
+* --vad-max-speech-duration-s: Maximum speech duration in seconds. Speech segments
+longer than this will be automatically split into multiple segments at silence
+points exceeding 98ms to prevent excessively long segments.
+
+* --vad-speech-pad-ms: Speech padding in milliseconds. Adds this amount of padding
+before and after each detected speech segment to avoid cutting off speech edges.
+
+* --vad-samples-overlap: Amount of audio to extend from each speech segment into
+the next one, in seconds (e.g., 0.10 = 100ms overlap). This ensures speech isn't
+cut off abruptly between segments when they're concatenated together.
+
 ## Examples
 
 There are various examples of using the library for different projects in the [examples](examples) folder.