diff --git a/README.md b/README.md
index 12364c1..c53e274 100644
--- a/README.md
+++ b/README.md
@@ -17,11 +17,13 @@ There are two main types of audio datasets: speech datasets and audio event/musi
 * [CREMA-D](https://github.com/CheyneyComputerScience/CREMA-D) - CREMA-D is a data set of 7,442 original clips from 91 actors. These clips were from 48 male and 43 female actors between the ages of 20 and 74 coming from a variety of races and ethnicities (African America, Asian, Caucasian, Hispanic, and Unspecified).
 * [DAPS Dataset](https://archive.org/details/daps_dataset) - DAPS consists of 20 speakers (10 female and 10 male) reading 5 excerpts each from public domain books (which provides about 14 minutes of data per speaker). 
 * [Deep Clustering Dataset](https://www.merl.com/demos/deep-clustering) - Training deep discriminative embeddings to solve the cocktail party problem.
+* [DIPCO](https://arxiv.org/abs/1909.13447) - Dinner Party Corpus - The participants were recorded by a single-channel close-talk microphone and by five far-field 7-microphone array devices positioned at different locations in the recording room. The dataset contains the audio recordings and human labeled transcripts of a total of 10 sessions with a duration between 15 and 45 minutes. 
 * [Emotional Voices Database](https://github.com/numediart/EmoV-DB) - various emotions with 5 voice actors (amused, angry, disgusted, neutral, sleepy).
 * [Emotional Voice dataset - Nature](https://www.nature.com/articles/s41562-019-0533-6) -  2,519 speech samples produced by 100 actors from 5 cultures. With large-scale statistical inference methods, we find that prosody can communicate at least 12 distinct kinds of emotion that are preserved across the 2 cultures. 
 * [Free Spoken Digit Dataset](https://github.com/Jakobovski/free-spoken-digit-dataset) -4 speakers, 2,000 recordings (50 of each digit per speaker), English pronunciations.
 * [Flickr Audio Caption](https://groups.csail.mit.edu/sls/downloads/flickraudio/) - 40,000 spoken captions of 8,000 natural images, 4.2 GB in size.
 * [ISOLET Data Set](https://data.world/uci/isolet) - This 38.7 GB dataset helps predict which letter-name was spoken — a simple classification task.
+* [Libri-CSS](https://github.com/chenzhuo1011/libri_css) - derived from LibriSpeech by concatenating the corpus utterances to simulate a conversation and capturing the audio replays with far-field microphones.
 * [LibriMix](https://github.com/JorisCos/LibriMix) - LibriMix is an open source dataset for source separation in noisy environments. It is derived from LibriSpeech signals (clean subset) and WHAM noise. It offers a free alternative to the WHAM dataset and complements it. It will also enable cross-dataset experiments.
 * [Librispeech](https://www.openslr.org/12) - LibriSpeech is a corpus of approximately 1000 hours of 16Khz read English speech derived from read audiobooks from the LibriVox project.
 * [LJ Speech](https://keithito.com/LJ-Speech-Dataset/) - This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading passages from 7 non-fiction books. A transcription is provided for each clip. Clips vary in length from 1 to 10 seconds and have a total length of approximately 24 hours.