Add examples for Kotlin API (#124)

kotlin-api-examples/Main.kt

@@ -0,0 +1,57 @@
+package com.k2fsa.sherpa.onnx
+
+import android.content.res.AssetManager
+
+fun main() {
+    var featConfig = FeatureConfig(
+        sampleRate = 16000,
+        featureDim = 80,
+    )
+
+    // please refer to
+    // https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
+    // to dowload pre-trained models
+    var modelConfig = OnlineTransducerModelConfig(
+        encoder = "./sherpa-onnx-streaming-zipformer-en-2023-02-21/encoder-epoch-99-avg-1.onnx",
+        decoder = "./sherpa-onnx-streaming-zipformer-en-2023-02-21/decoder-epoch-99-avg-1.onnx",
+        joiner = "./sherpa-onnx-streaming-zipformer-en-2023-02-21/joiner-epoch-99-avg-1.onnx",
+        tokens = "./sherpa-onnx-streaming-zipformer-en-2023-02-21/tokens.txt",
+        numThreads = 1,
+        debug = false,
+    )
+
+    var endpointConfig = EndpointConfig()
+
+    var config = OnlineRecognizerConfig(
+        modelConfig = modelConfig,
+        featConfig = featConfig,
+        endpointConfig = endpointConfig,
+        enableEndpoint = true,
+        decodingMethod = "greedy_search",
+        maxActivePaths = 4,
+    )
+
+    var model = SherpaOnnx(
+        config = config,
+    )
+
+    var objArray = WaveReader.readWaveFromFile(
+        filename = "./sherpa-onnx-streaming-zipformer-en-2023-02-21/test_wavs/0.wav",
+    )
+    var samples : FloatArray = objArray[0] as FloatArray
+    var sampleRate : Int = objArray[1] as Int
+
+    model.acceptWaveform(samples, sampleRate=sampleRate)
+    while (model.isReady()) {
+      model.decode()
+    }
+
+    var tailPaddings = FloatArray((sampleRate * 0.5).toInt()) // 0.5 seconds
+    model.acceptWaveform(tailPaddings, sampleRate=sampleRate)
+    model.inputFinished()
+    while (model.isReady()) {
+      model.decode()
+    }
+
+    println("results: ${model.text}")
+}