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README.md
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README.md
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# ESP-SR Speech Recognition Framework
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[](https://docs.espressif.com/projects/esp-sr/zh_CN/latest/esp32/index.html)
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[](https://docs.espressif.com/projects/esp-sr/en/latest/esp32s3/index.html)
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Espressif `ESP-SR <https://github.com/espressif/esp-sr>`_ helps users build AI speech solutions based on ESP32 or ESP32-S3 chips.
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Espressif [ESP-SR](https://github.com/espressif/esp-sr) helps users build AI speech solutions based on ESP32 or ESP32-S3 chips.
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Overview
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--------
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ESP-SR framework includes the following modules:
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* Audio Front-end AFE
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* Wake Word Engine WakeNet
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* Speech Command Word Recognition MultiNet
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* [Audio Front-end AFE](https://docs.espressif.com/projects/esp-sr/en/latest/esp32s3/audio_front_end/README.html)
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* [Wake Word Engine WakeNet](https://docs.espressif.com/projects/esp-sr/en/latest/esp32s3/wake_word_engine/README.html)
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* [Speech Command Word Recognition MultiNet](https://docs.espressif.com/projects/esp-sr/en/latest/esp32s3/speech_command_recognition/README.html)
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* Speech Synthesis (only supports Chinese language)
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These algorithms are provided in the form of a component, so they can be integrated into your projects with minimum effort.
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Flash Model
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===========
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Flashing Models
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===============
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:link_to_translation:`zh_CN:[中文]`
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ESP-SR's WakeNet and MultiNet both use a lot of model data (which can be found in :project:`model`). Currently, ESP-SR supports the following methods to flash models:
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In the AI industry, a model refers to a mathematical representation of a system or process. It is used to make predictions or decisions based on input data. There are many types of models, such as decision trees, neural networks, and support vector machines, each with their own strengths and weaknesses. Esprssif also provides our trained models such as WakeNet and MultiNet (see the model data used in :project:`model`)
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To use our models in your project, you need to flash these models. Currently, ESP-SR supports the following methods to flash models:
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.. only:: esp32
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@ -17,7 +17,7 @@ ESP-SR User Guide
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Audio Front-end (AFE) <audio_front_end/index>
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Wake Word WakeNet <wake_word_engine/index>
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Speech Command Word MultiNet <speech_command_recognition/README>
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Flash Model <flash_model/README>
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Flashing Models <flash_model/README>
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Resource Overhead <benchmark/README>
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Test Report <test_report/README>
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Glossary <glossary/glossary>
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@ -35,7 +35,7 @@ The following table shows the models supported by Espressif SoCs:
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| English | | | | √ |
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+---------+-----------+-------------+---------------+-------------+
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For details on flash models, see Section :doc:`flash model <../flash_model/README>` .
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For details on flash models, see Section :doc:`Flashing Models <../flash_model/README>` .
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.. note::
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Models ending with Q8 represents the 8 bit version of the model, which is more lightweight.
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@ -77,7 +77,7 @@ Use WakeNet
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- Select WakeNet model
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To select WakeNet model, please refer to Section :doc:`flash model <../flash_model/README>` .
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To select WakeNet model, please refer to Section :doc:`Flashing Models <../flash_model/README>` .
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To customize wake words, please refer to Section :doc:`Espressif Speech Wake-up Solution Customization Process <ESP_Wake_Words_Customization>`
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@ -3,7 +3,9 @@
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:link_to_translation:`en:[English]`
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ESP-SR 的 WakeNet 和 MultiNet 均会使用大量的模型数据,模型数据位于 :project:`model` 中。目前 ESP-SR 支持以下模型加载方式:
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在人工智能行业中,模型是指一个系统或过程的数学表示。它用于基于输入数据做出预测或决策,有许多不同类型的模型,如决策树、神经网络和支持向量机,每种模型都有其优缺点。乐鑫也提供经过训练的 WakeNet 和 MultiNet 模型(数据模型见 :project:`model`) 。
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使用模型前需先将其加载至你的项目,目前 ESP-SR 支持以下模型加载方式:
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.. only:: esp32
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