WhisperBridge provides on-device speech-to-text using Whisper models. Its API is intentionally small: initialize a model, transcribe a WAV file, and release resources when done.

Platform support#

Current support in the library code:

• Android: supported
• iOS: supported
• JVM / Desktop: supported
• WASM: currently not implemented

Public API#

expect object WhisperBridge {
    fun getModelPath(modelFileName: String): String
    fun initModel(modelPath: String): Boolean
    fun transcribeWav(wavPath: String, language: String? = null): String
    fun release()
}

getModelPath(modelFileName)#

Returns a platform-usable path for the Whisper model file.

val modelPath = WhisperBridge.getModelPath("ggml-base.en.bin")

initModel(modelPath)#

Loads the Whisper model and prepares the transcription context.

val ok = WhisperBridge.initModel(modelPath)
check(ok) { "Failed to initialize Whisper model" }

Call this once before transcription.

transcribeWav(wavPath, language)#

Transcribes a WAV audio file into text.

val text = WhisperBridge.transcribeWav(
    wavPath = "/path/to/sample.wav",
    language = "en"
)
println(text)

Parameters#

• wavPath: path to the WAV file to transcribe
• language: optional language hint such as "en", "es", or "fr"

If you already know the language, providing it can improve predictability and reduce ambiguity.

Return value#

Returns the transcription as a String. If transcription fails, the result may be empty.

Supported input expectations#

The bridge API is WAV-oriented, so the simplest and most reliable flow is:

1. record or load audio
2. convert it to WAV if necessary
3. call transcribeWav(...)

If your app records audio in another format, perform a conversion step before calling the bridge.

release()#

Releases native Whisper resources.

WhisperBridge.release()

Practical recommendations#

• Keep audio clean and reasonably short when testing.
• Normalize your pipeline around WAV files for fewer surprises.
• Reuse the initialized model when transcribing multiple files.
• Release resources when leaving the speech feature or shutting the app down.