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Update documentation of micro_speech example #38753

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Update documentation of micro_speech example #38753

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9502277
Update README.md of micro_speech example
biagiom Apr 21, 2020
8bcb69a
Update training documentation related to micro_speech example
biagiom Apr 21, 2020
d0c4a04
Merge branch 'master' into update_doc_micro_speech
biagiom May 5, 2020
09cc976
Merge branch 'master' into update_doc_micro_speech
biagiom May 12, 2020
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14 changes: 7 additions & 7 deletions tensorflow/lite/micro/examples/micro_speech/README.md
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Expand Up @@ -27,10 +27,10 @@ kilobytes of Flash.

## Deploy to Arduino

The following instructions will help you build and deploy this sample
The following instructions will help you build and deploy this example
to [Arduino](https://www.arduino.cc/) devices.

The sample has been tested with the following devices:
The example has been tested with the following devices:

- [Arduino Nano 33 BLE Sense](https://store.arduino.cc/usa/nano-33-ble-sense-with-headers)

Expand Down Expand Up @@ -84,11 +84,11 @@ If you don't see any output, repeat the process again.

## Deploy to ESP32

The following instructions will help you build and deploy this sample to
The following instructions will help you build and deploy this example to
[ESP32](https://www.espressif.com/en/products/hardware/esp32/overview) devices
using the [ESP IDF](https://github.com/espressif/esp-idf).

The sample has been tested on ESP-IDF version 4.0 with the following devices: -
The example has been tested on ESP-IDF version 4.0 with the following devices: -
[ESP32-DevKitC](http://esp-idf.readthedocs.io/en/latest/get-started/get-started-devkitc.html) -
[ESP-EYE](https://github.com/espressif/esp-who/blob/master/docs/en/get-started/ESP-EYE_Getting_Started_Guide.md)

Expand Down Expand Up @@ -139,7 +139,7 @@ monitor`

## Deploy to SparkFun Edge

The following instructions will help you build and deploy this sample on the
The following instructions will help you build and deploy this example on the
[SparkFun Edge development board](https://sparkfun.com/products/15170).

The program will toggle the blue LED on and off with each inference. It will
Expand Down Expand Up @@ -288,7 +288,7 @@ followed by the `K` key, then hit the `Y` key.

## Deploy to STM32F746

The following instructions will help you build and deploy the sample to the
The following instructions will help you build and deploy the example to the
[STM32F7 discovery kit](https://os.mbed.com/platforms/ST-Discovery-F746NG/)
using [ARM Mbed](https://github.com/ARMmbed/mbed-cli).

Expand Down Expand Up @@ -392,7 +392,7 @@ followed by the `K` key, then hit the `Y` key.

## Deploy to NXP FRDM K66F

The following instructions will help you build and deploy the sample to the
The following instructions will help you build and deploy the example to the
[NXP FRDM K66F](https://www.nxp.com/design/development-boards/freedom-development-boards/mcu-boards/freedom-development-platform-for-kinetis-k66-k65-and-k26-mcus:FRDM-K66F)
using [ARM Mbed](https://github.com/ARMmbed/mbed-cli).

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14 changes: 7 additions & 7 deletions tensorflow/lite/micro/examples/micro_speech/train/README.md
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Expand Up @@ -39,8 +39,8 @@ tutorial.

## Overview

1. Dataset: Speech Commands, Version 2. ([Download Link](https://storage.cloud.google.com/download.tensorflow.org/data/speech_commands_v0.02.tar.gz)
, [Paper](https://arxiv.org/abs/1804.03209))
1. Dataset: Speech Commands, Version 2. ([Download Link](https://storage.cloud.google.com/download.tensorflow.org/data/speech_commands_v0.02.tar.gz),
[Paper](https://arxiv.org/abs/1804.03209))
2. Dataset Type: **Speech**
3. Deep Learning Framework: **TensorFlow 1.5**
4. Language: **Python 3.7**
Expand Down Expand Up @@ -75,11 +75,11 @@ The `models` directory in the above zip file can be generated by following the
instructions in the [Training](#training) section above. It
includes the following 3 model files:

| Name | Format | Target Framework | Target Device |
| :------------- |:-------------|:-------------|-----|
| `model.pb` | Frozen GraphDef | TensorFlow | Large-Scale/Cloud/Servers |
| `model.tflite` *(<20 kB)* | Fully Quantized* TFLite Model | TensorFlow Lite | Mobile Devices|
| `model.cc` | C Source File | TensorFlow Lite for Microcontrollers | Microcontrollers |
| Name | Format | Target Framework | Target Device |
| :------------------------ | :---------------------------- | :----------------------------------- | :------------------------ |
| `model.pb` | Frozen GraphDef | TensorFlow | Large-Scale/Cloud/Servers |
| `model.tflite` *(<20 kB)* | Fully Quantized* TFLite Model | TensorFlow Lite | Mobile Devices |
| `model.cc` | C Source File | TensorFlow Lite for Microcontrollers | Microcontrollers |

**Fully quantized implies that the model is **strictly int8** quantized
**including** the input(s) and output(s).*
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