.Ensure compatibility with a number of platforms, including.NET 6.0,. NET Framework 4.6.2, and.NET Criterion 2.0 and also above.Reduce dependencies to prevent model conflicts and the demand for tiing redirects.Transcribing Sound Record.Some of the major capabilities of the SDK is actually audio transcription. Programmers can easily transcribe audio data asynchronously or in real-time. Below is an instance of exactly how to transcribe an audio documents:.using AssemblyAI.using AssemblyAI.Transcripts.var customer = brand-new AssemblyAIClient(" YOUR_API_KEY").var transcript = wait for 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 reports, comparable code may be made use of to obtain transcription.await making use of var stream = brand new FileStream("./ nbc.mp3", FileMode.Open).var records = await client.Transcripts.TranscribeAsync(.flow,.new TranscriptOptionalParams.LanguageCode = TranscriptLanguageCode.EnUs.).transcript.EnsureStatusCompleted().Console.WriteLine( transcript.Text).Real-Time Audio Transcription.The SDK additionally holds real-time sound transcription utilizing Streaming Speech-to-Text. This feature is especially beneficial for treatments requiring prompt handling of audio records.making use of AssemblyAI.Realtime.wait for making use of var scribe = brand new RealtimeTranscriber( brand new RealtimeTranscriberOptions.ApiKey="YOUR_API_KEY",.SampleRate = 16_000. ).transcriber.PartialTranscriptReceived.Subscribe( records =>Console.WriteLine($" Limited: transcript.Text "). ).transcriber.FinalTranscriptReceived.Subscribe( records =>Console.WriteLine($" Ultimate: transcript.Text "). ).wait for transcriber.ConnectAsync().// Pseudocode for obtaining audio coming from a mic as an example.GetAudio( async (portion) => wait for transcriber.SendAudioAsync( portion)).wait for transcriber.CloseAsync().Making Use Of LeMUR for LLM Functions.The SDK incorporates with LeMUR to make it possible for programmers to construct big language design (LLM) functions on voice records. Listed here is an instance:.var lemurTaskParams = brand new LemurTaskParams.Motivate="Offer a quick recap of the records.",.TranscriptIds = [transcript.Id],.FinalModel = LemurModel.AnthropicClaude3 _ 5_Sonnet..var action = wait for client.Lemur.TaskAsync( lemurTaskParams).Console.WriteLine( response.Response).Audio Intelligence Styles.Additionally, the SDK comes with built-in help for audio cleverness models, making it possible for sentiment evaluation and other innovative components.var records = wait for client.Transcripts.TranscribeAsync( brand-new TranscriptParams.AudioUrl="https://storage.googleapis.com/aai-docs-samples/nbc.mp3",.SentimentAnalysis = true. ).foreach (var result in transcript.SentimentAnalysisResults!).Console.WriteLine( result.Text).Console.WriteLine( result.Sentiment)// FAVORABLE, NEUTRAL, or NEGATIVE.Console.WriteLine( result.Confidence).Console.WriteLine($" Timestamp: result.Start - result.End ").For additional information, see the official AssemblyAI blog.Image resource: Shutterstock.