ios

Orca Streaming Text-to-Speech Engine

Made in Vancouver, Canada by Picovoice

Orca is an on-device streaming text-to-speech engine that is designed for use with LLMs, enabling zero-latency voice assistants. Orca is:

• Private; All speech synthesis runs locally.
• Cross-Platform:
  • Linux (x86_64), macOS (x86_64, arm64), Windows (x86_64)
  • Android and iOS
  • Chrome, Safari, Firefox, and Edge
  • Raspberry Pi (3, 4, 5)

Compatibility

• iOS 13.0 or higher

Installation

The Orca iOS binding is available via Cocoapods. To import it into your iOS project, add the following line to your Podfile and run pod install:

pod 'Orca-iOS'

AccessKey

Orca requires a valid Picovoice AccessKey at initialization. AccessKey acts as your credentials when using Orca SDKs. You can get your AccessKey for free. Make sure to keep your AccessKey secret. Signup or Login to Picovoice Console to get your AccessKey.

Usage

Orca supports two modes of operation: streaming and single synthesis. In the streaming synthesis mode, Orca processes an incoming text stream in real-time and generates audio in parallel. In the single synthesis mode, a complete text is synthesized in a single call to the Orca engine.

Create an instance of the Orca engine:

import Orca

let accessKey : String = // .. accessKey provided by Picovoice Console (https://console.picovoice.ai/)

let modelPath = Bundle(for: type(of: self)).path(
        forResource: "${MODEL_FILE}", // Name of the model file name for Orca
        ofType: "pv")!

do {
    let orca = try Orca(accessKey: accessKey, modelPath: modelPath)
} catch { }

Alternatively, you can provide modelPath as an absolute path to the model file on device.

To synthesize a text stream, create an Orca.OrcaStream object and add text to it one-by-one:

let orcaStream = try orca.streamOpen()

for textChunk in textGenerator() {
  let pcm = orcaStream.synthesize(textChunk)
  if pcm != nil {
    // handle pcm
  }
}

let pcm = orcaStream.flush()
if pcm != nil {
  // handle pcm
}

The textGenerator() function can be any stream generating text, for example an LLM response. Orca produces audio chunks in parallel to the incoming text stream, and returns the raw PCM whenever enough context has been added via orcaStream.synthesize(). To ensure smooth transitions between chunks, the orcaStream.synthesize() function returns an audio chunk that only includes the audio for a portion of the text that has been added. To generate the audio for the remaining text, orcaStream.flush() needs to be invoked. When done with streaming text synthesis, the Orca.OrcaStream object needs to be closed:

orcaStream.close()

If the complete text is known before synthesis, single synthesis mode can be used to generate speech in a single call to Orca:

// Return raw PCM and alignments
let (pcm, wordArray) = try orca.synthesize(text: "${TEXT}")

// Save the generated audio to a WAV file directly
let wordArray = try orca.synthesizeToFile(text: "${TEXT}", outputPath: "${OUTPUT_PATH}")

Replace ${TEXT} with the text to be synthesized and ${OUTPUT_PATH} with the path to save the generated audio as a single-channel 16-bit PCM WAV file. In single synthesis mode, Orca returns metadata of the synthesized audio in the form of an array of OrcaWord objects. When done, resources have to be released explicitly:

orca.delete()

Text input

Orca supports a wide range of English characters, including letters, numbers, symbols, and punctuation marks. You can get a list of all supported characters by calling validCharacters(). Pronunciations of characters or words not supported by this list can be achieved with custom pronunciations.

Custom pronunciations

Orca allows to embed custom pronunciations in the text via the syntax: {word|pronunciation}.
The pronunciation is expressed in ARPAbet phonemes, for example:

• "This is a {custom|K AH S T AH M} pronunciation"
• "{read|R IY D} this as {read|R EH D}, please."
• "I {live|L IH V} in {Sevilla|S EH V IY Y AH}. We have great {live|L AY V} sports!"

Voices

Orca can synthesize speech with various voices, each of which is characterized by a model file located in lib/common. To create an instance of the engine with a specific voice, use:

import Orca

do {
    let orca = try Orca(accessKey: accessKey, modelPath: "${MODEL_FILE_PATH}")
    // or
    let orca = try Orca(accessKey: accessKey, modelURL: "${MODEL_FILE_URL}")
} catch { }

and replace ${MODEL_FILE_PATH} or ${MODEL_FILE_URL} with the path to the model file with the desired voice.

Speech control

Orca allows for keyword arguments to control the synthesized speech. They can be provided to the streamOpen method or the single synthesis methods synthesize and synthesizeToFile:

• speechRate: Controls the speed of the generated speech. Valid values are within [0.7, 1.3]. A higher (lower) value produces speech that is faster (slower). The default is 1.0.
• randomState: Sets the random state for sampling during synthesis. This can be used to ensure that the synthesized speech is deterministic across different runs.

let pcm = orca.synthesize(
    text: "${TEXT}",
    speechRate: 1.0,
    randomState: 1)

Orca properties

To obtain the set of valid characters, call Orca.validCharacters. To retrieve the maximum number of characters allowed, call Orca.maxCharacterLimit. The sample rate of Orca is Orca.sampleRate.

Alignment Metadata

Along with the raw PCM or saved audio file, Orca returns metadata for the synthesized audio in single synthesis mode. The OrcaWord object has the following properties:

• Word: String representation of the word.
• Start Time: Indicates when the word started in the synthesized audio. Value is in seconds.
• End Time: Indicates when the word ended in the synthesized audio. Value is in seconds.
• Phonemes: An array of OrcaPhoneme objects.

The OrcaPhoneme object has the following properties:

• Phoneme: String representation of the phoneme.
• Start Time: Indicates when the phoneme started in the synthesized audio. Value is in seconds.
• End Time: Indicates when the phoneme ended in the synthesized audio. Value is in seconds.

Running Unit Tests

Copy your AccessKey into the accessKey variable in OrcaAppTestUITests.swift. Open OrcaAppTest.xcworkspace with XCode and run the tests with Product > Test.

Demo App

For example usage refer to our iOS demo application.