voice: Canary 180M as a middle choice for the final words

gearslip/src/main/java/app/seb3thehacker/gearslip/speech/SpeechEngine.kt

@@ -17,6 +17,7 @@ import app.seb3thehacker.gearslip.audio.CarMic
 import com.k2fsa.sherpa.onnx.EndpointConfig
 import com.k2fsa.sherpa.onnx.EndpointRule
 import com.k2fsa.sherpa.onnx.FeatureConfig
+import com.k2fsa.sherpa.onnx.OfflineCanaryModelConfig
 import com.k2fsa.sherpa.onnx.OfflineModelConfig
 import com.k2fsa.sherpa.onnx.OfflineRecognizer
 import com.k2fsa.sherpa.onnx.OfflineRecognizerConfig
@@ -284,12 +285,21 @@ object SpeechEngine {
             OfflineRecognizer(
                 config = OfflineRecognizerConfig(
                     featConfig = FeatureConfig(sampleRate = RATE, featureDim = 80),
-                    modelConfig = OfflineModelConfig(
+                    modelConfig = if (model.modelType == "canary") {
-                        transducer = OfflineTransducerModelConfig(path(model.encoder), path(model.decoder), path(model.joiner)),
+                        // English in, English out, and no punctuation: clean() strips it anyway.
-                        tokens = path("tokens.txt"),
+                        OfflineModelConfig(
-                        numThreads = threads(),
+                            canary = OfflineCanaryModelConfig(path(model.encoder), path(model.decoder), srcLang = "en", tgtLang = "en", usePnc = false),
-                        modelType = model.modelType,
+                            tokens = path("tokens.txt"),
-                    ),
+                            numThreads = threads(),
+                        )
+                    } else {
+                        OfflineModelConfig(
+                            transducer = OfflineTransducerModelConfig(path(model.encoder), path(model.decoder), path(model.joiner)),
+                            tokens = path("tokens.txt"),
+                            numThreads = threads(),
+                            modelType = model.modelType,
+                        )
+                    },
                     decodingMethod = "greedy_search",
                 ),
             )

gearslip/src/main/java/app/seb3thehacker/gearslip/speech/SpeechModels.kt

@@ -31,6 +31,7 @@ object SpeechModels {
         private val archive: String,
         val encoder: String,
         val decoder: String,
+        /** Empty for Canary, which decodes with attention and has no joiner. */
         val joiner: String,
         val modelType: String = "",
     ) {
@@ -44,6 +45,11 @@ object SpeechModels {
             "sherpa-onnx-nemo-parakeet_tdt_transducer_110m-en-36000-int8",
             "encoder.int8.onnx", "decoder.int8.onnx", "joiner.int8.onnx", modelType = "nemo_transducer",
         ),
+        CANARY(
+            Role.FINAL, "canary-180m-en", "Canary", "In between: better than Parakeet small, quicker than large. NVIDIA NeMo, CC BY 4.0", 154,
+            "sherpa-onnx-nemo-canary-180m-flash-en-es-de-fr-int8",
+            "encoder.int8.onnx", "decoder.int8.onnx", "", modelType = "canary",
+        ),
         PARAKEET_LARGE(
             Role.FINAL, "parakeet-0.6b-en", "Parakeet large", "Recommended. Hears names and places best. NVIDIA NeMo, CC BY 4.0", 460,
             "sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8",
@@ -52,7 +58,7 @@ object SpeechModels {
         ;
 
         val url get() = "https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/$archive.tar.bz2"
-        val files get() = listOf(encoder, decoder, joiner, "tokens.txt")
+        val files get() = listOf(encoder, decoder, joiner, "tokens.txt").filter { it.isNotEmpty() }
     }
 
     sealed interface State {

gearslip/src/main/java/app/seb3thehacker/gearslip/ui/SupportViews.kt

@@ -155,7 +155,7 @@ internal fun AboutLinkRows() {
     SettingsRow(
         "Voice credits",
         subtitle = "Speech recognition by sherpa-onnx (Apache 2.0), with Kroko ASR by Banafo " +
-            "(CC BY-SA 4.0) and Parakeet by NVIDIA (CC BY 4.0)",
+            "(CC BY-SA 4.0), and Parakeet and Canary by NVIDIA (CC BY 4.0)",
         icon = Icons.Filled.Favorite,
     )
 }