From speech analytics to video subtitles, speech-to-text software brings new ideas to life. Leopard Speech-to-Text has created even more opportunities with cloud-level accuracy on the device, combining the best of the cloud and on-device processing.

Leopard Speech-to-Text, now officially supports seven new languages: French, German, Italian, Japanese, Korean, Portuguese, and Spanish. More developers can build private, reliable, cost-effective transcription software with production-ready, easy-to-use, and cross-platform Leopard Speech-to-Text.

Try It

The web demo below converts voice data to text in eight languages: English, French, German, Italian, Japanese, Korean, Portuguese, and Spanish. The demo runs within your web browser, meaning the audio is processed locally without using 3rd party cloud services. Transcribe an existing audio file or record a new one to see it yourself.

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Start Building Now

Building with intuitive and cross-platform Leopard Speech-to-Text SDKs doesn’t require any experience in Machine Learning. Anyone can start transcribing with a few lines of code.

leopard = pvleopard.create(access_key)
transcript, words = leopard.process_file(path)
Build with Python
const leopard = new Leopard(accessKey)
const { transcript, words } = leopard.processFile(path)
Build with NodeJS
Leopard leopard = new Leopard.Builder()
.setAccessKey(accessKey)
.setModelPath(modelPath)
.build(appContext);
LeopardTranscript result = leopard.processFile(path);
Build with Android
let leopard = Leopard(
accessKey: accessKey,
modelPath: modelPath)
let result = leopard.processFile(path)
Build with iOS
leopard = NewLeopard(accessKey)
err := leopard.Init()
transcript, words, err := leopard.ProcessFile(path)
Build with Go
Leopard leopard = new Leopard.Builder()
.setAccessKey(accessKey)
.build();
LeopardTranscript result = leopard.processFile(path);
Build with Java
Leopard leopard = Leopard.Create(accessKey);
LeopardTranscript result = leopard.ProcessFile(path);
Build with .NET
let leopard: Leopard = LeopardBuilder::new()
.access_key(access_key)
.init()
.expect("");
if let Ok(result) = leopard.process_file(path) { }
Build with Rust
Leopard leopard = await Leopard.create(
accessKey,
modelPath);
LeopardTranscript result = await leopard.processFile(path);
Build with Flutter
const leopard = await Leopard.create(
accessKey,
modelPath)
const {transcript, words} = await leopard.processFile(path)
Build with React Native
pv_leopard_t *leopard = NULL;
pv_leopard_init(
access_key,
model_path,
enable_automatic_punctuation,
&leopard);
char *transcript = NULL;
int32_t num_words = 0;
pv_word_t *words = NULL;
pv_leopard_process_file(
leopard,
path,
&transcript,
&num_words,
&words);
Build with C
const leopard = await LeopardWorker.fromPublicDirectory(
accessKey,
modelPath
);
const { transcript, words } = await leopard.process(pcm);
Build with Web

Train Use-case Specific Speech Models

Leopard Speech-to-Text offers cloud-level accuracy out-of-the-box. However, some use cases and industries, such as healthcare, finance, or legal, have special terminology that cannot be accurately predicted by generic speech models.

Custom Vocabulary & Keyword Boosting features allow developers to customize speech-to-text models specific to their application on the no-code Picovoice Console .

Automated Transcription in 8 Languages: Transcripción automática (Spanish), Transcrição automática (Portuguese), 자동 전사 (Korean), 自動文字起こし (Japanese), Trascrizione automatica (Italian), Automatische transkription (German), and Transcription automatique (French) Start Free