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)
- Android 5.0+ (API 21+)
Orca can be found on Maven Central. To include the package in your Android project, ensure you have
included mavenCentral()
in your top-level build.gradle
file and then add the following to your app's build.gradle
:
dependencies {
// ...
implementation 'ai.picovoice:orca-android:${LATEST_VERSION}'
}
Orca requires a valid Picovoice AccessKey
at initialization. AccessKey
acts as your credentials when using Orca
SDKs. You can get your AccessKey
for free. Make sure to keep your AccessKey
secret.
Signup or Login to Picovoice Console to get your AccessKey
.
To enable AccessKey validation, you must add the following line to your AndroidManifest.xml
file:
<uses-permission android:name="android.permission.INTERNET"/>
Orca supports two modes of operation: streaming and single synthesis. In the streaming synthesis mode, Orca processes an incoming text stream in real-time and generates audio in parallel. In the single synthesis mode, a complete text is synthesized in a single call to the Orca engine.
Create an instance of the engine with the Orca Builder class by passing in the accessKey, modelPath and Android app context:
import ai.picovoice.orca.*;
final String accessKey = "${ACCESS_KEY}"; // AccessKey provided by Picovoice Console (https://console.picovoice.ai/)
final String modelPath = "${MODEL_FILE_PATH}"; // path relative to the assets folder or absolute path to file (`.pv`) on device
try {
Orca orca = new Orca.Builder()
.setAccessKey(accessKey)
.setModelPath(modelPath)
.build(appContext);
} catch (OrcaException ex) { }
To synthesize a text stream, create an OrcaStream
object and add text to it one-by-one:
Orca.OrcaStream orcaStream = orca.streamOpen(new OrcaSynthesizeParams.Builder().build());
for (String textChunk : textGenerator()) {
short[] pcm = orcaStream.synthesize(textChunk);
if (pcm != null) {
// handle pcm
}
}
short[] flushedPcm = orcaStream.flush();
if (flushedPcm != null) {
// handle pcm
}
The textGenerator()
function can be any stream generating text, for example an LLM response.
Orca produces audio chunks in parallel to the incoming text stream, and returns the raw PCM whenever enough context has
been added via orcaStream.synthesize()
.
To ensure smooth transitions between chunks, the orcaStream.synthesize()
function returns an audio chunk that only
includes the audio for a portion of the text that has been added.
To generate the audio for the remaining text, orcaStream.flush()
needs to be invoked.
When done with streaming text synthesis, the OrcaStream
object needs to be closed:
orcaStream.close();
If the complete text is known before synthesis, single synthesis mode can be used to generate speech in a single call to Orca:
OrcaSynthesizeParams params = new OrcaSynthesizeParams.Builder().build();
// Return raw PCM and alignments
OrcaAudio audio = orca.synthesize("${TEXT}", params);
// Save the generated audio to a WAV file directly
OrcaWord[] orcaWords = orca.synthesizeToFile("${TEXT}", "${OUTPUT_PATH}", params);
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 make sure to explicitly release the resources using:
orca.delete()
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 getValidCharacters()
.
Pronunciations of characters or words not supported by this list can be achieved with
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!"
Orca can synthesize speech with various voices, each of which is characterized by a model file located in lib/common.
To add the Orca model file to your Android application:
- Download the desired voice model from the Orca GitHub repository.
- Add the model file as a bundled resource by placing it under the assets directory of your Android
project (
src/main/assets/
).
Orca allows you to control the synthesized speech via the OrcaSynthesizeParams
class. You can pass in additional
settings by using the nested Builder class:
import ai.picovoice.orca.*;
OrcaSynthesizeParams params = new OrcaSynthesizeParams.Builder()
.setSpeechRate(1.2f)
.setRandomState(1)
.build();
setSpeechRate()
: Controls the speed of the generated speech. Valid values are within [0.7, 1.3]. A higher value produces speech that is faster. The default is1.0
.setRandomState()
: Sets the random state for sampling during synthesis. This can be used to ensure that the synthesized speech is deterministic across different runs.
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.
To see Orca used in an app, refer to our Android demo app.