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@ -23,7 +23,7 @@ The new algorithms will no longer support ESP32 chips.
News
----
[28/3/2025]: We release **Sound Souce Localization**, an algorithm to locate the sound source.
[14/2/2025]: We release **ESP-SR V2.0**. [Migration from ESP-SR V1.* to ESP-SR V2.*](https://docs.espressif.com/projects/esp-sr/en/latest/esp32s3/audio_front_end/migration_guide.html)
[13/2/2025]: We release **VADNet**, a voice activaty detection model. You can use it to replace the WebRTC VAD and improve the performance.
@ -89,11 +89,15 @@ The following MultiNet models are supported in esp-sr:
## Audio Front End
Espressif Audio Front-End **AFE** integrates AEC (Acoustic Echo Cancellation), VAD (Voice Activity Detection), BSS (Blind Source Separation) and NS (Noise Suppression).
Espressif Audio Front-End **AFE** integrates AEC (Acoustic Echo Cancellation), VAD (Voice Activity Detection), BSS (Blind Source Separation) and NS (Noise Suppression), NSNET(Deep noise suppression), SSL(Sound Souce Localization) and other functions. It is designed to be used with the ESP-SR library.
Our two-mic Audio Front-End (AFE) have been qualified as a “Software Audio Front-End Solution” for [Amazon Alexa Built-in devices](https://developer.amazon.com/en-US/alexa/solution-providers/alexa-connect-kit).
**In order to achieve optimal performance:**
## Documentation and Resources
ESP-SR Documentation: [ESP-SR Documentation](https://docs.espressif.com/projects/esp-sr/en/latest/esp32s3/index.html)
Migration Guide: [Migration from V1.* to V2.*](https://docs.espressif.com/projects/esp-sr/en/latest/esp32s3/audio_front_end/migration_guide.html)
Wake Word Training: [Wake Word Training by TTS Pipeline V2.0](https://github.com/espressif/esp-sr/issues/88)
Examples: [esp-skainet/examples](https://github.com/espressif/esp-skainet)
* Please refer to software design [esp-skainet](https://github.com/espressif/esp-skainet).