.Make certain being compatible along with several platforms, including.NET 6.0,. Internet Platform 4.6.2, and.NET Standard 2.0 and above.Minimize dependencies to avoid variation problems and the requirement for tiing redirects.Transcribing Sound Record.Some of the primary functions of the SDK is audio transcription. Designers can translate audio reports asynchronously or in real-time. Below is an instance of just how to record an audio documents:.making use of AssemblyAI.using AssemblyAI.Transcripts.var client = new AssemblyAIClient(" YOUR_API_KEY").var transcript = wait for client.Transcripts.TranscribeAsync( new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3". ).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).For local reports, similar code may be utilized to obtain transcription.await utilizing var stream = 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 Audio Transcription.The SDK likewise sustains real-time sound transcription making use of Streaming Speech-to-Text. This attribute is actually particularly practical for treatments demanding quick handling of audio information.using AssemblyAI.Realtime.wait for making use of var transcriber = brand new RealtimeTranscriber( brand new RealtimeTranscriberOptions.ApiKey="YOUR_API_KEY",.SampleRate = 16_000. ).transcriber.PartialTranscriptReceived.Subscribe( records =>Console.WriteLine($" Partial: transcript.Text "). ).transcriber.FinalTranscriptReceived.Subscribe( records =>Console.WriteLine($" Final: transcript.Text "). ).await transcriber.ConnectAsync().// Pseudocode for acquiring audio coming from a mic for example.GetAudio( async (piece) => await transcriber.SendAudioAsync( piece)).await transcriber.CloseAsync().Taking Advantage Of LeMUR for LLM Applications.The SDK combines with LeMUR to permit developers to construct huge foreign language model (LLM) apps on voice records. Right here is actually an instance:.var lemurTaskParams = brand-new LemurTaskParams.Cue="Offer a quick summary of the records.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var reaction = wait for client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Audio Intelligence Models.Also, the SDK possesses built-in support for audio intelligence versions, permitting feeling analysis and also various other state-of-the-art features.var records = await client.Transcripts.TranscribeAsync( brand new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3",.SentimentAnalysis = accurate. ).foreach (var cause 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 ").To find out more, check out the main AssemblyAI blog.Image source: Shutterstock.