An audio processing system, comprising: an input interface configured to receive an audio signal; a memory configured to store a neural network trained to determine different types of attributes of multiple concurrent audio events of different origins, wherein the attributes define metadata of the multiple concurrent audio events of different origins, wherein the different types of attributes include time-dependent and time-agnostic attributes of speech and non-speech audio events, wherein the time-dependent attributes each include a transcription of speech, wherein the time-agnostic attributes include labels of the audio events and/or an audio caption describing an audio scene, wherein a model of the neural network shares at least some parameters for determining both types of the attributes, wherein the model of the neural network includes an encoder and a decoder, and wherein the parameters shared for determining different types of the attributes include parameters of the encoder; a processor configured to process the audio signal with the neural network to produce metadata of the audio signal, the metadata including one or multiple attributes of one or multiple audio events in the audio signal; and an output interface configured to output the metadata of the audio signal; wherein the neural network is trained jointly to perform multiple different transcription tasks using the shared parameters for performing each of the transcription tasks; and wherein the transcription tasks include an automatic speech recognition, ASR, task and an acoustic event detection, AED, task; characterized in that the model of neural network includes a transformer model and a connectionist temporal classification, CTC, based model, wherein the transformer model includes the encoder and the decoder, the encoder is configured to encode the audio signal and the decoder is configured to execute ASR decoding, AED decoding, and audio tagging, AT, decoding to produce a decoder output for the encoded audio signal, and wherein the CTC-based model is configured to execute the ASR decoding and the AED decoding, for the encoded audio signal, to produce a CTC output for the encoded audio signal, and wherein the decoder output and the CTC output of the ASR decoding and the AED decoding are jointly scored to produce a joint decoding output. an input interface configured to receive an audio signal; a memory configured to store a neural network trained to determine different types of attributes of multiple concurrent audio events of different origins, wherein the attributes define metadata of the multiple concurrent audio events of different origins, wherein the different types of attributes include time-dependent and time-agnostic attributes of speech and non-speech audio events, wherein the time-dependent attributes each include a transcription of speech, wherein the time-agnostic attributes include labels of the audio events and/or an audio caption describing an audio scene, wherein a model of the neural network shares at least some parameters for determining both types of the attributes, wherein the model of the neural network includes an encoder and a decoder, and wherein the parameters shared for determining different types of the attributes include parameters of the encoder; a processor configured to process the audio signal with the neural network to produce metadata of the audio signal, the metadata including one or multiple attributes of one or multiple audio events in the audio signal; and an output interface configured to output the metadata of the audio signal; wherein the neural network is trained jointly to perform multiple different transcription tasks using the shared parameters for performing each of the transcription tasks; and wherein the transcription tasks include an automatic speech recognition, ASR, task and an acoustic event detection, AED, task; characterized in that the model of neural network includes a transformer model and a connectionist temporal classification, CTC, based model, wherein the transformer model includes the encoder and the decoder, the encoder is configured to encode the audio signal and the decoder is configured to execute ASR decoding, AED decoding, and audio tagging, AT, decoding to produce a decoder output for the encoded audio signal, and wherein the CTC-based model is configured to execute the ASR decoding and the AED decoding, for the encoded audio signal, to produce a CTC output for the encoded audio signal, and wherein the decoder output and the CTC output of the ASR decoding and the AED decoding are jointly scored to produce a joint decoding output.