tf_speech 0.0.1

Flutter TensorFlow Speech #

pub package

The TensorFlow audio recognition tutorial, for use in flutter, with an API that you'll love to use!

var speech = TfSpeech();
await for (var result in speech.stream) {
  print(result);
}

Example app video

Source code.


How does this work?

We use Android's AudioRecord API to record audio in the smallest possible chunks.

These chunks are loaded into a ring buffer.

The ring buffer is periodically fed into the TensorFlow model for inference.

The raw output from the model is passed straight to dart, which allows for a great degree of control from dart code.


example/lib/main.dart

import 'dart:async';

import 'package:flutter/material.dart';
import 'package:permission_handler/permission_handler.dart';
import 'package:tf_speech/tf_speech.dart';

void main() => runApp(MyApp());

class MyApp extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      home: Scaffold(
        body: SafeArea(
          child: Home(),
        ),
      ),
    );
  }
}

class Home extends StatefulWidget {
  @override
  _HomeState createState() => _HomeState();
}

class _HomeState extends State<Home> {
  static const moveDelayMs = 10;
  static const moveDelta = 0.005;

  static const thresholds = {
    "up": 0.5,
    "down": 0.2,
    "left": 0.3,
    "right": 0.3,
    "stop": 0.5,
  };

  @override
  Widget build(BuildContext context) {
    return Stack(
      children: <Widget>[
        if (result.isNotEmpty)
          Positioned.fill(
            child: PredictionBar(
              thresholds: thresholds,
              values: result,
            ),
          ),
        Positioned.fill(
          child: Center(
            child: Transform.translate(
              offset: offset,
              child: Image.asset(
                'assets/rocket.png',
                width: 50,
              ),
            ),
          ),
        ),
      ],
    );
  }

  var speech = TfSpeech();
  var offset = Offset.zero;
  var result = <String, double>{};

  @override
  void initState() {
    super.initState();
    startRecognizer();
  }

  @override
  void dispose() {
    super.dispose();
    speech.close();
  }

  Future<void> startRecognizer() async {
    if (!await Permission.speech.request().isGranted) return;

    Timer timer;

    await for (result in speech.stream) {
      if (!mounted) return;
      setState(() {});

      // select keywords that pass the threshold, and move accordingly
      for (var entry in thresholds.entries) {
        if (result[entry.key] < entry.value) continue;

        switch (entry.key) {
          case "up":
            timer?.cancel();
            timer = createTimer(deltaY: -moveDelta);
            break;
          case "down":
            timer?.cancel();
            timer = createTimer(deltaY: moveDelta);
            break;
          case "right":
            timer?.cancel();
            timer = createTimer(deltaX: moveDelta);
            break;
          case "left":
            timer?.cancel();
            timer = createTimer(deltaX: -moveDelta);
            break;
          case "stop":
            timer?.cancel();
            break;
          default:
            break;
        }
        break;
      }
    }
  }

  Timer createTimer({double deltaX: 0, double deltaY: 0}) {
    return Timer.periodic(Duration(milliseconds: moveDelayMs), (_) {
      var size = MediaQuery.of(context).size;

      var dx = wrapValue(offset.dx + size.width * deltaX, size.width / 2);
      var dy = wrapValue(offset.dy + size.height * deltaY, size.height / 2);

      setState(() {
        offset = Offset(dx, dy);
      });
    });
  }
}

double wrapValue(double dx, double max) {
  if (dx < -max) {
    dx = max;
  } else if (dx > max) {
    dx = -max;
  }
  return dx;
}

class PredictionBar extends StatelessWidget {
  final Map<String, double> values;
  final double height, width;
  final Map<String, double> thresholds;

  const PredictionBar({
    Key key,
    @required this.values,
    @required this.thresholds,
    this.height = 80,
    this.width = 10,
  }) : super(key: key);

  @override
  Widget build(BuildContext context) {
    var theme = Theme.of(context);
    return Center(
      child: SingleChildScrollView(
        scrollDirection: Axis.horizontal,
        child: Row(
          mainAxisAlignment: MainAxisAlignment.center,
          children: <Widget>[
            for (var entry in values.entries)
              if (thresholds.containsKey(entry.key))
                Padding(
                  padding: EdgeInsets.all(5),
                  child: Column(
                    children: <Widget>[
                      Container(
                        height: height,
                        width: width,
                        decoration: BoxDecoration(
                          borderRadius: BorderRadius.circular(10),
                          border: Border.all(color: theme.dividerColor),
                        ),
                        alignment: Alignment.bottomLeft,
                        child: Container(
                          decoration: BoxDecoration(
                            borderRadius: BorderRadius.circular(10),
                            color: entry.value < thresholds[entry.key]
                                ? theme.disabledColor
                                : theme.primaryColor,
                          ),
                          height: entry.value * height,
                        ),
                      ),
                      SizedBox(height: 10),
                      RotatedBox(
                        quarterTurns: 3,
                        child: Text(
                          entry.key,
                          style: TextStyle(fontSize: 18),
                        ),
                      ),
                    ],
                  ),
                )
          ],
        ),
      ),
    );
  }
}

Use this package as a library

1. Depend on it

Add this to your package's pubspec.yaml file:


dependencies:
  tf_speech: ^0.0.1

2. Install it

You can install packages from the command line:

with Flutter:


$ flutter pub get

Alternatively, your editor might support flutter pub get. Check the docs for your editor to learn more.

3. Import it

Now in your Dart code, you can use:


import 'package:tf_speech/tf_speech.dart';
  
Popularity:
Describes how popular the package is relative to other packages. [more]
45
Health:
Code health derived from static analysis. [more]
100
Maintenance:
Reflects how tidy and up-to-date the package is. [more]
56
Overall:
Weighted score of the above. [more]
63
Learn more about scoring.

We analyzed this package on Jul 11, 2020, and provided a score, details, and suggestions below. Analysis was completed with status completed using:

  • Dart: 2.8.4
  • pana: 0.13.14
  • Flutter: 1.17.5

Analysis suggestions

Package does not support Flutter platform linux

Because:

  • package:tf_speech/tf_speech.dart that declares support for platforms: android, ios

Package does not support Flutter platform macos

Because:

  • package:tf_speech/tf_speech.dart that declares support for platforms: android, ios

Package does not support Flutter platform web

Because:

  • package:tf_speech/tf_speech.dart that declares support for platforms: android, ios

Package does not support Flutter platform windows

Because:

  • package:tf_speech/tf_speech.dart that declares support for platforms: android, ios

Package not compatible with SDK dart

Because:

  • tf_speech that is a package requiring null.

Maintenance issues and suggestions

Provide a file named CHANGELOG.md. (-20 points)

Changelog entries help developers follow the progress of your package. See the example generated by stagehand.

The package description is too short. (-12 points)

Add more detail to the description field of pubspec.yaml. Use 60 to 180 characters to describe the package, what it does, and its target use case.

Package is pre-v0.1 release. (-10 points)

While nothing is inherently wrong with versions of 0.0.*, it might mean that the author is still experimenting with the general direction of the API.

Update README.md. (-2 points)

1 image link is insecure (e.g. http://img.youtube.com/vi/USiOuBkVEIs/0.jpg), use https URLs instead.

Dependencies

Package Constraint Resolved Available
Direct dependencies
Dart SDK >=2.1.0 <3.0.0
flutter 0.0.0
plugin_scaffold ^3.1.0 3.1.0
Transitive dependencies
collection 1.14.12 1.14.13
meta 1.1.8 1.2.2
sky_engine 0.0.99
typed_data 1.1.6 1.2.0
vector_math 2.0.8 2.1.0-nullsafety
Dev dependencies
flutter_test