.Guarantee compatibility with various frameworks, including.NET 6.0,. Internet Structure 4.6.2, and.NET Criterion 2.0 and above.Reduce dependencies to prevent model conflicts as well as the demand for binding redirects.Translating Audio Information.Some of the main performances of the SDK is actually audio transcription. Programmers may record audio files asynchronously or in real-time. Below is actually an instance of just how to translate an audio documents:.using AssemblyAI.making use of AssemblyAI.Transcripts.var client = brand new AssemblyAIClient(" YOUR_API_KEY").var records = await client.Transcripts.TranscribeAsync( brand new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3". ).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).For local area data, similar code can be made use of to achieve transcription.await using var flow = brand new FileStream("./ nbc.mp3", FileMode.Open).var transcript = await client.Transcripts.TranscribeAsync(.flow,.brand new TranscriptOptionalParams.LanguageCode = TranscriptLanguageCode.EnUs.).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).Real-Time Sound Transcription.The SDK also supports real-time sound transcription making use of Streaming Speech-to-Text. This function is especially practical for applications demanding quick processing of audio data.making use of AssemblyAI.Realtime.wait for making use of var scribe = brand-new RealtimeTranscriber( new RealtimeTranscriberOptions.ApiKey="YOUR_API_KEY",.SampleRate = 16_000. ).transcriber.PartialTranscriptReceived.Subscribe( transcript =>Console.WriteLine($" Partial: transcript.Text "). ).transcriber.FinalTranscriptReceived.Subscribe( transcript =>Console.WriteLine($" Ultimate: transcript.Text "). ).wait for transcriber.ConnectAsync().// Pseudocode for acquiring audio from a microphone for example.GetAudio( async (piece) => wait for transcriber.SendAudioAsync( portion)).wait for transcriber.CloseAsync().Using LeMUR for LLM Apps.The SDK combines with LeMUR to permit developers to create sizable language style (LLM) functions on voice records. Here is an example:.var lemurTaskParams = new LemurTaskParams.Prompt="Offer a short conclusion of the transcript.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var feedback = wait for client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Audio Cleverness Models.Also, the SDK comes with built-in assistance for audio intellect models, making it possible for sentiment analysis as well as various other advanced features.var transcript = await client.Transcripts.TranscribeAsync( brand-new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3",.SentimentAnalysis = correct. ).foreach (var lead to transcript.SentimentAnalysisResults!).Console.WriteLine( result.Text).Console.WriteLine( result.Sentiment)// POSITIVE, NEUTRAL, or downside.Console.WriteLine( result.Confidence).Console.WriteLine($" Timestamp: result.Start - result.End ").For additional information, visit the main AssemblyAI blog.Image resource: Shutterstock.