Open-source speech recognition + TTS for iPhone (1) Welcome to openears

Openears is an open-source speech recognition + TTS library, which has been used in several iPhone apps. The latest upgrade has improved the code efficiency and upgraded it to xcode4. There is an openears tutorial on the politepix website. The following is a repost. Please try again later.

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Welcome to openears!

Openears is an open-source IOS library for implementing round-trip
English language speech recognition and text-to-speech on the iPhone and
IPad, which uses the CMU pocketsph.pdf
, CMU Flite
, And mitlm
Libraries.

The current version of openears is 0.91
.

This version has a number of changes under the hood and two API
Changes for existing api cils, so if you want to stick with
Previous Version 0.9.02 for now, you can still download it here
And it contains all of the old support documents as PDFs as well. I'll
Support 0.9.0.2 until it's clear that 0.91 is as stable as 0.9.02-
Please just identify which version you are using when seeking support.

Openears. 91 can:

• Listen continuously for speech on a background thread,
  While suspending or resuming speech processing on demand, all while
  Using less than 8% CPU on average on a first-generation iPhone (Decoding
  Speech, text-to-speech, updating the UI and other intermittent
  Functions use more CPU ),
• Use any of 8 voices for speech and switch between them on the fly,
• Know whether headphones are plugged in and continue voice recognition during text-to-speech only when they are plugged in,
• Support Bluetooth audio devices (very experimental in this version ),
• Dispatch information to any part of your app about
  Results of speech recognition and speech, or changes in the state of
  Audio SESSION (such as an incoming phone call or headphones being
  Plugged In ),
• Deliver level metering for both speech input and speech output so you can design visual feedback for both States.
• Support jsgf grammars,
• Dynamically generate new ARPA language models in-app based on input from an nsarray of nsstrings,
• Switch between ARPA language models on the fly,
• Be easily interacted with via standard and simple objective-C methods,
• Control all audio functions with text-to-speech and
  Speech recognition in memory instead of writing audio files to disk and
  Then reading them,
• Drive speech recognition with a low-latency audio unit driver for highest responsiveness,
• Be installed in a cocoa-Standard fashion using static
  Library projects that, after initial configuration, allow you to target
  Or re-target any sdks or ubuntures that are supported by
  Libraries (verified as going back to SDK 3.1.2 at least) by making
  Changes to your main project only.

In addition to its various new features and faster
Recognition/text-to-speech responsiveness, openears now has improved
Recognition accuracy.

Before using openears, please note that its new low-latency audio
Unit driver is not compatible with the simulator, so it has a fallback
Audio queue driver for the simulator provided as a convenience so you
Can debug recognition logic. This means is that recognition is better on
The device, and that I 'd appreciate it if bug reports are limited
Issues which affect the device.

To use openears:

1. Begin with "getting started with openears
"Which will explain how to set up the libraries your app will make use.

2. Then read "processing ing your app for openears
"Which will explain how to make the openears libraries available to your app projects, and lastly,

3. You'll be ready for "Using openears in your app
"Which will explain the objects and methods that will be available to your app and how to use them.

If those steps give you trouble, you can check out the support and FAQ
Page.