Prepare Round 1 model profile QA baseline

Ariver

2026-06-02 3fbceec8de833416bf1ae049f959f222c3f1a4a0

 privatevoice.src/internal/engine/engine_linux.go

File was renamed from VoiceSnapGo/internal/engine/engine_linux.go
@@ -5,9 +5,10 @@
import (
   "fmt"
   "voicesnap/internal/logger"
   "voicesnap/internal/model"

   sherpa "github.com/k2-fsa/sherpa-onnx-go/sherpa_onnx"
   _ "github.com/k2-fsa/sherpa-onnx-go-linux"
   sherpa "github.com/k2-fsa/sherpa-onnx-go/sherpa_onnx"
)

type sherpaEngine struct {
@@ -15,18 +16,15 @@
   hwInfo     string
}

func newPlatformEngine() (Engine, error) {
   modelPath := ModelPath()
   tokensPath := TokensPath()

func newPlatformEngine(resolved model.ResolvedModel) (Engine, error) {
   // Linux: CPU only
   config := sherpa.OfflineRecognizerConfig{}
   config.FeatConfig.SampleRate = 16000
   config.FeatConfig.FeatureDim = 80
   config.ModelConfig.SenseVoice.Model = modelPath
   config.ModelConfig.SenseVoice.Model = resolved.Files["model"]
   config.ModelConfig.SenseVoice.UseInverseTextNormalization = 1
   config.ModelConfig.Tokens = tokensPath
   config.ModelConfig.NumThreads = 4
   config.ModelConfig.Tokens = resolved.Files["tokens"]
   config.ModelConfig.NumThreads = resolved.Profile.NumThreads
   config.ModelConfig.Provider = "cpu"
   config.DecodingMethod = "greedy_search"