Outdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchPC Slower Than It Used to Be?
A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Oído is an open-source speech-to-text engine designed to transcribe spoken sentences on an ESP32-S3, rather than recognize only a fixed list of commands. Lokutor says it runs on-device without cloud inference or a neural accelerator. Its documented target is a specific ESP32-S3 memory configuration, and its published benchmark results are project-reported—not measurements of real-time speed on a physical board.
What Oído does—and what “without a command list” means
Many embedded voice systems are command recognizers: they listen for phrases from a predefined set and map them to actions. Espressif describes MultiNet as offline speech command recognition supporting up to 300 Chinese or English commands. Oído instead aims to turn open-vocabulary speech into text, so the speaker is not limited to choosing from a command list. The tasks differ, so their benchmark figures are not directly equivalent. Lokutor’s Oído repository and October 1, 2026 launch announcement describe the project as local speech-to-text; Espressif documents MultiNet in its ESP-SR repository.
As an Amazon Associate I earn from qualifying purchases.
The project name comes from “¡Oído!”, a Spanish kitchen expression used to confirm that an order was heard. Oído’s repository lists English and Spanish model files. It does not list a bilingual model, so the languages use separate files.
Hardware required to run it on the board
The documented target is an ESP32-S3 N16R8: 16 MB of flash and 8 MB of octal PSRAM. The setup instructions name an ESP32-S3-DevKitC-1 N16R8 and an INMP441 I2S microphone. An ESP32-S3 board name alone does not confirm that the memory configuration is present, so check the exact board specification before choosing hardware.
#1 Best Overall
- 🔥【Dual Mode & High Performance】 The ESP32-S3 development board features integrated dual-core xtensa 32-bit LX7 microprocessor, clock speed up to 240 MHz, with 16MB Flash and 8 MB PSRAM. Perfect for Arduino IoT projects requiring stable wireless communication with ultra-low power consumption.
- 🔧【Easy Programming & Debugging】 Equipped with dual USB Type-C ports, this ESP32-S3 board supports both USB and UART modes for effortless programming, firmware flashing, and debugging.
- 🌐【Versatile Wireless Connectivity】 Built-in Wi-Fi (2.4GHz) and Bluetooth 5.0 (LE) dual-mode ensure seamless connectivity with a wide range of smart devices, making it ideal for IoT, smart homes projects.
- 🚀【Flexible Download Options】 Supports dual download methods — USB direct download or USB-to-serial download — offering flexibility and convenience for different development needs.Ideal for beginners and developers working with ESP32-S3.
- 🔋【Advanced Power-Saving Modes】 Designed for energy-efficient applications, with 3.3V SPI voltage, the ESP32-S3 board supports multiple low-power modes, allowing you to extend battery life based on different usage scenarios.
- Required microphone: INMP441 I2S, with SCK to GPIO4, WS to GPIO5, SD to GPIO6, and L/R to ground.
- Optional display: a 0.96-inch SSD1306 OLED, with SDA to GPIO8 and SCL to GPIO9. It displays the live transcript but is not a prerequisite.
These board and wiring details are from the Oído repository setup instructions. The repository also provides a host build, CLI, and live microphone demo, allowing a reader to try the software without the ESP32-S3 board. The launch announcement lists Python dependencies including NumPy, soundfile, SentencePiece, and sounddevice; use the project’s current instructions for the exact build and run commands.
Choosing an English model profile
Word error rate (WER) measures transcription errors against a reference transcript; a lower value indicates fewer errors. The following figures are reported by Lokutor’s repository, with status dated October 2, 2026. They are not independent replications. “Test-clean” and “test-other” are LibriSpeech evaluation splits, so compare profiles within those same splits rather than treating the numbers as universal accuracy guarantees.
Rank #2
- ESP32-S3-DevKitC-1-N16R8 SPI voltage: 3.3v, ESP32-S3-DevKitC-1 is an entry-level development board equipped with Wi-Fi + Bluetooth module ESP32-S3
- Most of the I/O pins on the module are broken out to the pin headers on both sides of this board for easy interfacing. Developers can either connect peripherals with jumper wires or mount ESP32-S3-DevKitC on a breadboard.
- The ESP32-S3-DevKitC development board equipped with ESP32-S3-DevKitC-1-N16R8, a general-purpose Wi-Fi + Bluetooth LE MCU module that integrates complete Wi-Fi and Bluetooth LE functions.
- ESP32-S3-N16R8 cable can be used: USB Type A to Type-C cable or CC cable Note the distinction between the commonly used USB A port to Type-C cable that can only be charged, which cannot be used for communication between YD-ESP32-S3 and the host.
- USB-to-UART Port and ESP32-S3 USB Port (either one or both), default power supply (recommended)
| Profile | Reported WER | What changes |
|---|---|---|
| Int8, greedy decoding | 3.7% test-clean; 8.2% test-other | Baseline listed profile; model file is 14.0 MB. |
| Int8, language model and beam search | 3.3% test-clean; 7.2% test-other | Best English WER listed; optional language model adds 1.3 MB. |
| Int4, greedy decoding | 4.6% test-clean; 10.0% test-other | Smaller model file, 8.3 MB; trades some reported accuracy for lower flash use. |
| Int4 with language model | 3.8% test-clean; 8.4% test-other | Improves the reported int4 WER; the optional language model adds 1.3 MB. |
| Streaming English with language model | 4.9% test-clean; 11.0% test-other | Produces partial text while speech is in progress, with lower reported accuracy than the listed utterance-oriented profiles. |
All values and model sizes in this table are from the repository status dated October 2, 2026. The practical choice depends on the available flash, tolerance for transcription errors, and whether text must appear during speech or can wait until the utterance ends.
Free tools Windows power users keep installed
One-click scans. No signup required.
Spanish results and language limits
For its Spanish model with the language model, Lokutor reports WER of 13.3% on Common Voice, 10.6% on Multilingual LibriSpeech, 15.5% on VoxPopuli, and 11.3% on FLEURS. These are project-reported results across different datasets, not a single directly comparable score; the repository does not establish an equivalent English-versus-Spanish test. English and Spanish are the languages listed in the current model table, and the language models are separate files. The repository’s model and benchmark table contains the reported figures.
Rank #3
- 【Low-power performance】: The AYWHP ESP32-S3 Core development board integrates a 2.4 GHz Wi-Fi and Bluetooth 5 (LE) dual-mode communication module, perfect for Arduino Internet of Things (IoT) projects.
- 【Simple programming and debugging】: The ESP32-S3 module makes it easy to program and burn in your ESP32-S3 board via dual USB Type-C ports, with a choice of USB or UART modes.
- 【Multiple Power Saving Modes】: The ESP S3 development board supports multiple low-power modes, which can be configured according to different application scenarios to provide longer battery life.
- 【Dual download modes】: The ESP S3-1 module supports both USB direct connection download and USB to serial port download, providing more flexibility and convenience.
- 【Diverse connectivity options】: The ESP32-S3-1 supports dual-mode Wi-Fi and Bluetooth 5.0 (LE) connectivity for a wide range of smart devices, making it ideal for Internet of Things (IoT) applications.
What the performance claims establish
Lokutor’s October 2, 2026 repository status says the accuracy evaluation uses the host build of the engine, which compiles the same C code as the firmware. The project reports that firmware transcripts in Espressif’s QEMU emulator matched the host on most utterances, while numerical rounding differences can affect some difficult, noisy clips.
That validation is not a published physical-board speed test. The repository says real-time speed is estimated from emulator instruction counts and that physical-board measurements were still pending in the status note. The October 1 launch announcement likewise says its demo transcripts are sped up and that physical-board footage was forthcoming. The sources therefore support host and emulator validation, but not a claim that the published demo proves real-time operation on a physical ESP32-S3. Repository status; launch announcement.
Rank #4
- 【ESP32-S3 PERFORMANCE】Dual-core 240MHz processor with 16MB Flash and 8MB PSRAM for IoT, AI, and machine learning projects.
- 【WIRELESS CONNECTIVITY】Onboard antenna for 2.4GHz WiFi and Bluetooth 5.0 LE — for smart home devices, no external antenna needed.
- 【LEAD-FREE GOLD EDITION DESIGN】Immersion gold (ENIG) plating for durability and conductivity. Lead-free, RoHS-compliant — for long-term prototyping.
- 【PRE-SOLDERED, PLUG-IN DESIGN】ESP32-S3 boards come with pre-soldered headers and plug directly into the included expansion and terminal boards — no soldering required.
- 【MULTI-PLATFORM COMPATIBILITY】Works with C++, MicroPython, ESP-IDF, Raspberry Pi, and STM32 — with online tutorials for quick start. Power via USB-C (5V) or VIN pin (5–12V); do not exceed 5V on the USB-C ports.
Trade-offs and known limitations
- Output timing: utterance mode returns text after speech ends; streaming mode can show partial text sooner but has lower reported accuracy.
- Acoustic conditions: the project identifies very noisy crowds and reverberant rooms as difficult cases.
- Hardware memory: the documented board setup requires the N16R8 configuration, not just any ESP32-S3.
- Language selection: English and Spanish use separate model files; no bilingual model is listed.
- Benchmark interpretation: WER results are project-reported, use particular datasets, and do not establish performance for every microphone, room, speaker, or physical-board runtime.
Licensing and commercial products
The repository identifies the code as GNU GPLv3, but the model files have their own licenses. It lists nemo8.tnm and the Spanish model and language model under CC-BY-4.0; nemo4.tnm and the English streaming model under CC-BY-SA-4.0; and the optional English language model under CC-BY-4.0. Check the license of each code and model file you distribute or use.
Lokutor says it offers commercial licenses and support for products that cannot meet GPLv3 terms, such as consumer devices that do not let users install modified firmware. The reviewed project sources do not state commercial-license pricing or eligibility. Product makers can contact Lokutor for terms. Repository licensing notes; launch announcement.
Quick Recap
Best Value
- 【GOLD EDITION — IMMERSION GOLD PCB】The Lonely Binary Gold Edition features a black PCB with lead-free immersion gold (ENIG) plating and clear silkscreen — the signature finish of the Lonely Binary Gold Edition line. RoHS-compliant.
- 【16MB FLASH + 8MB PSRAM】Large memory capacity for OTA updates, large programs, and AI/ML tasks — more headroom than 4MB boards for data-intensive IoT and automation projects.
- 【EXTERNAL IPEX ANTENNA】External IPEX antenna can be positioned for extended WiFi and Bluetooth signal coverage — for remote applications like weather stations, robots, or enclosed builds.
- 【DUAL USB TYPE-C PORTS】Separate power and data ports for macOS, Windows, and Linux. Power via USB-C (5V) or VIN pin (5–12V); do not exceed 5V on the USB-C ports.
- 【FLEXIBLE PROTOTYPING PINS】2x40-pin GPIO headers compatible with breadboards and sensors. Supports external ToF sensors via I2C for distance sensing.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
