From 49b421a9cdff5e9ff1342e94d1f6ae40c7914b40 Mon Sep 17 00:00:00 2001
From: Dimitrii Voronin <36505480+adamnsandle@users.noreply.github.com>
Date: Thu, 27 Jun 2024 19:12:27 +0300
Subject: [PATCH] Update README.md
---
README.md | 25 ++++++++++++++++++-------
1 file changed, 18 insertions(+), 7 deletions(-)
diff --git a/README.md b/README.md
index 056b121..b9853bf 100644
--- a/README.md
+++ b/README.md
@@ -13,7 +13,7 @@
-
+
@@ -38,20 +38,16 @@ https://user-images.githubusercontent.com/36505480/144874384-95f80f6d-a4f1-42cc-
- **Lightweight**
- JIT model is around one megabyte in size.
+ JIT model is around two megabytes in size.
- **General**
- Silero VAD was trained on huge corpora that include over **100** languages and it performs well on audios from different domains with various background noise and quality levels.
+ Silero VAD was trained on huge corpora that include over **6000** languages and it performs well on audios from different domains with various background noise and quality levels.
- **Flexible sampling rate**
Silero VAD [supports](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics#sample-rate-comparison) **8000 Hz** and **16000 Hz** [sampling rates](https://en.wikipedia.org/wiki/Sampling_(signal_processing)#Sampling_rate).
-- **Flexible chunk size**
-
- Model was trained on **30 ms**. Longer chunks are supported directly, others may work as well.
-
- **Highly Portable**
Silero VAD reaps benefits from the rich ecosystems built around **PyTorch** and **ONNX** running everywhere where these runtimes are available.
@@ -60,6 +56,21 @@ https://user-images.githubusercontent.com/36505480/144874384-95f80f6d-a4f1-42cc-
Published under permissive license (MIT) Silero VAD has zero strings attached - no telemetry, no keys, no registration, no built-in expiration, no keys or vendor lock.
+
+Fast start
+
+
+```python3
+import torch
+torch.set_num_threads(1)
+
+model, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad', model='silero_vad')
+(get_speech_timestamps, _, read_audio, _, _) = utils
+
+wav = read_audio('path_to_audio_file')
+speech_timestamps = get_speech_timestamps(wav, model)
+```
+
Typical Use Cases