# US 2018/0324293 A1 · Call recording > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2018/0324293 A1 - Document ID: US20180324293A1 - Status: Published application - Kind: A1 - Application number: 15/763,642 - Filed: 2016-09-29 - Published: 2018-11-08 - Earliest claimed: 2015-09-30 - Assignees: British Telecommunications public limited company - Applicants: British Telecommunications Public Limited Company - Inventors: Andrew DAVIS; Robert CLAXTON - Web page: https://patentgrep.com/patent/US20180324293A1 ## CPC - H04M 3/42221: {Conversation recording systems (at the subscriber's set H04M1/656)} - G10L 17/16: Hidden Markov models [HMM] - G10L 19/018: Audio watermarking, i.e. embedding inaudible data in the audio signal - H04M 3/51: Centralised call answering arrangements requiring operator intervention {, e.g. call or contact centers for telemarketing} - H04M 3/568: {audio processing specific to telephonic conferencing, e.g. spatial distribution, mixing of participants (echo suppression in two-way loud-speaking telephone systems H04M9/02; sound field processing per se H04S7/30)} - G10L 17/00: Speaker identification or verification techniques - H04M 2203/301: Management of recordings - H04M 2203/303: Marking - H04M: TELEPHONIC COMMUNICATION (circuits for controlling other apparatus via a telephone cable and not involving telephone switching apparatus G08) - G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING ## Abstract An enterprise voice system such as a contact centre is disclosed which provides a speech analytics capability. Whilst call recording is common in many contact centres, calls are normally recorded in single-channel audio files in order to save costs. Previous attempts to provide automatic diarization of those recorded calls have relied on training the system to recognise voiceprints of users of the system, and then comparing utterances within the recorded calls to those voiceprints in order to identify who was speaking at that time. In order to avoid the need to train the system to recognise voiceprints, an enterprise voice system is disclosed which inserts a digital watermark into the digitised audio signal from each user's microphone. By inserting the digital watermark with an energy, and, in some cases also with a spectrum, which matches the digitised audio signal, and taking advantage of typically only one user speaking at a time, a mark is left in the recorded call which a speech analytics system can use in order to identify who was speaking at different times in the conversation. ## Claims ### Claim 1 A method of generating a single-channel audio signal representing a multi-party conversation, said method comprising: receiving a plurality of audio signals representing the voices of respective participants in the multi-party conversation, and for at least one of the participants, marking the audio signal representing the participant's voice, at least when they are speaking, by: i) finding the current energy in the audio signal representing the participant's voice; ii) generating a speaker-dependent signal having an energy proportional to the current energy in the audio signal representing the participant's voice; and iii) adding said speaker-dependent signal to the audio signal representing the participant's voice to generate a marked audio signal; generating a single-channel audio signal by summing said at least one marked audio signal and any of said plurality of audio signals which have not been marked. ### Claim 2 (depends on 1) A method according to claim 1 wherein said speaker-dependent signal is generated from a predetermined speaker identification signal. ### Claim 3 (depends on 2) A method according to claim 2 wherein the generation of said speaker-dependent signal comprises scaling said predetermined speaker-identifying signal, or a portion thereof, added over an energy analysis time period by an amount proportional to the energy found in the audio signal representing the participant's voice over said energy analysis time period. ### Claim 4 (depends on 1) A method according to claim 1 where said speaker identification, speaker-dependent and audio signals comprise digital signals. ### Claim 5 (depends on 4) A method according to claim 4 wherein said speaker identification signal comprises a digital watermark. ### Claim 6 (depends on 4) A method according to claim 4 wherein said speaker identification signal comprises a pseudo-random bit sequence. ### Claim 7 (depends on 6) A method according to claim 6 wherein said speaker identification signal comprises a maximal length sequence. ### Claim 8 (depends on 4) A method according to claim 4 further comprising: finding the spectral shape of said audio signal over a spectral analysis time period, said speaker-dependent signal generation comprising spectrally shaping said speaker-identification signal, or a portion thereof, to generate a speaker-dependent signal whose spectrum is similar to the spectrum of said audio signal over said spectral analysis time period. ### Claim 9 (depends on 8) A method according to claim 8 wherein: finding the spectral shape of said audio signal comprises calculating linear prediction coding coefficients for the audio signal; and spectrally shaping said speaker-identification signal comprises passing the speaker-identification signal through a linear prediction synthesis filter configured with said calculated linear prediction coding coefficients. ### Claim 10 (depends on 1) A method of recording a multi-party conversation comprising generating a single-channel audio signal representing the multi-party conversation using the method of claim 1, and recording said single-channel audio signal. ### Claim 11 (depends on 1) A method of processing an audio signal to identify a current speaker, said audio signal having been generated using the method of claim 1, said method comprising processing said signal to recognise the presence of a speaker-dependent signal in said signal. ### Claim 12 (depends on 11) A method according to claim 11 wherein said processing comprises: passing said single-channel audio signal through a linear prediction analysis filter to remove predictable elements of said single-channel audio signal; and carrying out a correlation analysis looking for correlations with said one or more speaker-dependent signals in order to recognise the presence of a given speaker-dependent signal in said single-channel audio signal.