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    1. Home
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    3. esp32-pie-asr
    esp32-pie-asr icon

    esp32-pie-asr

    Speech Recognition

    On-device live English speech recognition and voice-control demos for the ESP32-P4, running without cloud or a neural accelerator.

    Visit Website

    At a Glance

    Pricing
    Open Source

    Apache-2.0 licensed code for live English speech recognition on the ESP32-P4; model weights are separately licensed CC-BY-SA 4.0.

    Engagement

    Available On

    Windows
    macOS
    Linux
    Web
    API

    Resources

    WebsiteGitHubllms.txt

    Topics

    Speech RecognitionVoice ControlLocal Inference

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    Developer
    Boumedine Billal

    Listed Nov 2026

    About esp32-pie-asr

    esp32-pie-asr is an open-source project by Boumedine Billal that runs live English speech recognition on the ESP32-P4 microcontroller. The board's microphone feeds a streaming model and the recognized words appear on the board's screen as you speak, with no cloud. The firmware can be flashed from a browser page using Chrome or Edge.

    What It Is

    The project is embedded firmware plus an inference engine for the ESP32-P4X. It uses Kroko (by Banafo), a 65.7M-parameter streaming Zipformer2 transducer, with weights reduced from 71 MB to 26.65 MB using 2- and 4-bit quantization. Inference runs on the chip's two RISC-V cores using PIE SIMD instructions, with no neural accelerator. The firmware opens on live transcription and has a second page of six voice-control demos.

    Recognition and Voice Control

    The README reports 4.34% WER on LibriSpeech test-clean and 10.26% on test-other, at 0.70x real time, with words final about 2 seconds after they are spoken. A text file on the microSD card lists phrases (hotwords) to listen for, which can be toggled on screen without retraining. The six voice-control demos (robot vacuum, smart home, car cabin, factory line, kitchen, presenter) map spoken orders to simulated device actions using word rules rather than a language model.

    Setup Path

    The model file is copied to a FAT32 microSD card, since it does not fit the board's 16 MB flash. The browser installer then flashes the firmware over the USB Serial/JTAG port. It requires an ESP32-P4X-Function-EV-Board (chip revision v3). Alternatively, the firmware can be built with ESP-IDF v6.1. The code is Apache-2.0 and the weights are CC-BY-SA 4.0.

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    Pricing

    OPEN SOURCE

    Open Source

    Apache-2.0 licensed code for live English speech recognition on the ESP32-P4; model weights are separately licensed CC-BY-SA 4.0.

    • Code licensed under Apache-2.0
    • Model weights licensed CC-BY-SA 4.0 (as Kroko's), not Apache-2.0
    • Browser-based firmware flashing from the project page
    • Live English transcription and six voice-control demos
    • Requires ESP32-P4X-Function-EV-Board and a FAT32 microSD card (external hardware costs)

    Capabilities

    Key Features

    • Streaming on-device English speech recognition
    • No cloud and no neural accelerator
    • 2/4-bit quantized Kroko model (26.65 MB)
    • PIE SIMD kernels in assembly across both RISC-V cores
    • Custom phrase lists (hotwords) editable on microSD card
    • Six voice-control demos driven by word rules
    • Browser-based firmware flashing from Chrome or Edge
    • Bit-exact results between PC build and chip
    • Beam search decoding

    Integrations

    ESP-IDF
    Hugging Face
    Kroko
    sherpa-onnx
    API Available

    Demo Video

    esp32-pie-asr Demo Video
    Watch on YouTube

    Ratings & Reviews

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    Developer

    Boumedine Billal

    Read more about Boumedine Billal
    GitHub
    1 tool in directory

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